AUTOMOTIVEJOURNAL
2O23 + VOLUME 1

Your Battery Validation Lab Is
Already Obsolete. Or Is It?

Safe like a Robot.
Drives like a Human.

Making (and Testing) theWorld’s Greenest Battery

ni.com/automotiveEvolving with
Our Industry
For many, the natural evolution of theannual calendar brings about notions ofchange. Life springs back from wintry
conditions, resolutions of better self-care,and typically a much-needed break fromthe pace of “normal” and an opportunity
to relax with those we love and gain
perspective. For Automotive leaders,
however, this feels all too familiar.
Collectively, the automotive industry
has some momentum. The cost of theelectric powertrain continues to fall,
EV sales are expected to surpass 25
percent of total sales, and the technology
world looked to CES to showcase newpromises of innovation. That’s not all thatfeels familiar. Economists are predictinga recession, COVID-19 variants continue
to cause challenges, and automotive
leaders are still looking to extract value
from their data across the business todrive down cost and increase quality.
While much is changing, much remains thesame. What else is new? Dr. W. Edwards
Deming once wrote, “Survival is notcompulsory. Improvement is not compulsory.
But improvement is necessary for survival.”
If you’re ready for a change,
there is a better way.

Let us show you how.
02

03

Table of Contents
Battery Validation
06 YourLab Is Already Obsolete. Or Is It?
Modernize your lab to conquer speed, cost,and volume challenges.

Data Management
14 Better
Starts Here
Improve your data collection, analytics, anddecision-making processes.

like a Robot.
16 SafeDrives like a Human.
Jaguar Land Rover partners with NI toachieve a data-driven approach to validation.

(and Testing) the
20 MakingWorld’s Greenest Battery
Northvolt is optimizing battery performanceand closing the loop, sustainably.

Innovation Centers
24 NIaroundthe Globe
NI solutions help foster our customers’
industry-leading innovations.

04

Test Coverage with Your
26 Maximize
ADAS/AD Replay and HIL Test Systemz

Real-world and virtual test efforts can help
autonomous vehicles become a reality.

a Critical Coverage Gap
28 Closing
in ADAS/AD Camera Validation
Enable testing production release softwarewith real-time emulation like never before.

and Scalable
32 Flexible
EV Battery Cycler
Scale operations with easily synchronized,
orchestrated, and operated lab equipment.

Solutions
34 Mobility
for a Better Tomorrow
New shifts in automotive technology will
require adaptive, integrated solutions.

Dos and Don’ts of
40 TheWorking the Data andSoftware Connected Workflow
Avoid pitfalls through lessons learned
and get to the right solution faster.

05

Your Battery
Validation Lab Is
Already Obsolete.
Or Is It?
Have you been in a situation in which what you
think you know is strongly challenged?
A few weeks ago, I was showcasing NI’s battery validation
lab solutions to a diverse group of people and one of thebest questions I got was spot on. Where is the novelty?
I appreciated how the question framed the NI solution in adifferent context and made me restate the problem we’resolving: obsolescence. In the context of a battery validation lab,calling it obsolete is harsh because any recently built lab stillworks to find design flaws and ensure battery safety. However,
we constantly hear from the engineers we work with that labs
quickly become insufficient as demands for speed, cost, andvolume of work get tougher. So rather than obsolete, let’s consider
what makes a lab insufficient and explore what’s missing.

“Using NI’s Battery
Test System,
we made a very
sophisticated setup
I wouldn’t havebeen able to dowith anything elsein the expedited
timeframe required.”
Danny Marshall,
Test and Evaluation Team Leader,
Battery Innovation Center

Typical Battery Validation Lab Challenges
The fundamental components ofa battery validation lab include thecyclers to inject and draw powerfrom the batteries, the measurement
and instrumentation equipment, thechamber to ensure environmental and/or safety conditions over the test, andthe software that runs the whole test cell.

the test on the batteries. Such lab setup
is entirely possible, albeit fragmented,
but brings challenges such as:All these components are alreadycommercially available, include softwareinterfaces, return some sort of data,and can be integrated—at the rightcost—to operate together and perform

06

FEATURE ARTICLE



Inconsistent data storage practices
Manual asset management
Inconsistent software approach
Too many instrument and system types
Limited automation
Inconsistent test methodologies

FEATURE ARTICLE

07

“We get the openness to integrate
existing assets and proprietary
protocols, so we can maximize
reusability of our existing
equipment and speed up test.”
Henrik Rudelius,
Director, Validation and Simulation, Battery Systems,
Northvolt

The real problem though, comes in the form of limited productinsight, high engineering costs, and slower developmenttime. The consequences of these challenges vary from caseto case depending on the engineering resources available
or the level of investment possible. Another factor is the risktolerance to a “test enough” approach in which all regulations
and requirements are met, but there are no extended
efforts to optimize the battery performance and the test
operations. In summary, individual companies will have to finda reason to want to change their test and lab setup approachin line with the potential consequences of inaction.
Just like a typical lab setup could be sufficient for a given
company (although we do not see that often), optimization
may mean different things for different battery suppliers

08

FEATURE ARTICLE

and OEMs. We can make the safe assumption that there’s
always something to optimize and improve, but there’s nosingle way of modernizing a battery lab. How do we go about
optimization when so many things could be optimized?
The answer: software and data.

PROBLEM

WHY IT’S PAINFUL FOR THE TYPICAL LAB

HOW IT’S SOLVED IN THE MODERN LAB

Too many changes,
too fast

Making changes to individual
equipment is resource intensive.

Common software toolchain with out-of-the-box functionality
is used to automate tasks for cycler operation, taking
measurements, and reporting on test results.

Disruptions tolong test process

Test can’t be effectively simulated
before running—and once running,it’s not monitored as one, so
errors or failures in execution
are not timely detected, wastingtime and causing test reruns.

Real-time hardware provides reliability in execution
while test software continuously monitors test conditions
to timely trigger alarms and corrective actions.

Too much to
manage aslab grows

Lack of centralized lab operation
generates confusion and inconsistencies
in test execution, forcing timeintensive manual work to schedule,run, and report on test, as well as
monitor equipment utilization.

A higher-level software layer oversees all assets
alongside test and operational data, providing laboratory
information management system (LIMS) functions on a serverbased platform. It also helps define tests independently
from equipment using hardware abstraction and optimizes
utilization and operational costs through facility
monitoring.

Batteries are
difficult tounderstand

Data is stored inconsistently,
generating manual work to aggregate,report on, and make sense of it toderive insights. It also slows down
the feedback to the right stakeholders
to make design decisions from a clear
understanding of battery behavior.

A data-centric solution can ingest any format of datafrom any tool, contextualize it, and create web-based
dashboards on demand through standard visualization tools.
Any stakeholder can review test data, perform analysis,
and make decisions from it. Automation can be programmed
for anomaly detection and timely reporting on faults.

From Insufficient to Modern
Modernizing a battery validation lab is not about equipment,interfaces, or services, but about the value it brings
to the test operations. For example, some of the mostcommon requests we hear from customers seeking to
optimize their battery validation operations are:







Increasing automation to reducing manual work
Providing a common solution across battery cells,
modules, and packs
Integrating to existing equipment to continue
leveraging investments
Providing on-demand data access to all relevant stakeholders

This is no easy task—and we’ve found that a comprehensive
set of features like flexibility, openness, scalability, anddeterministic hardware synchronization are required to set
such a lab up for success. These features are invariably
enabled by a software- and data-centric approach to the lab,and particularly targeted to the most painful problems:

FEATURE ARTICLE

09

Software for the Modern Battery Test Lab
Connected Data—From Instruments to Insight—Accelerates Time-to-Market, Improves Product Performance

How to Move toward
Modernizing the Lab
Now that we understand what would take a battery
validation lab from quickly becoming insufficient to being
modern, comes the big question: how do we do it?

Improve the Product
Data Analytics

EFFICIENCYOUTPUTData

QUALITY

TIME
TO MARKET

ActionThe first big decision to make is what needs to be optimized.
Very similar to standardization, modernizing a battery
validation lab is a complex process that targets problems
in a systematic way to avoid unnecessary disruptions
and costs, while setting it up for long-term success.
There are generally three levels where the previously
described pain points would be (Figure 01). An inwardlooking analysis of where your current challenges aremost significant will guide you toward the first set of steps
to take. Some reference use cases to highlight are:

Run the Test:
Run the Lab
Data and System Management
ADMIN
TOOLS

Data

TEST
RESULTSUSERDASHBOARDS

ActionThe Battery Innovation Center (BIC) in Indiana is one of themost diverse customers we work with. Rather than scaling
up on one dimension (type of battery, type of test, etc.), theyrequire the ability to change test setups quickly and drastically,
for a myriad of batteries under test. BIC engineers can use
hardware abstraction layers, plugins, and other automated tools
to save time from configuration, setup, and reconfigurations
when responding to changes. Using the NI Battery Test System,
they’ve been able to reduce their setup times from weeks
to days, and quickly run tests as their customers require.

Run the Lab:Run the Test
Application Software

FIGURE 01
Software must enable the flow of data and commands to close the cycle from running the test, running the lab, and improving the product being tested.

Northvolt runs one of the most ambitious test operations as they
strive to make the world’s greenest battery. To run their labs, theyneeded openness to connect to existing equipment, program
proprietary protocols, and orchestrate the test so data can beused to improve their batteries, even after they’re deployed(read more on page 20). Future work will help optimize energy
usage, reduce CO2 footprint, increase utilization, better manage
downtimes, and ensure reliable data collection from the wholebattery test facility as well as the individual DUTs.

Improve the Product:
General Motors is betting big on their Ultium battery
platform; to scale up, they need accurate, on-demand
access to battery test data for their subject matter experts.
Working with NI solutions, they’ve saved thousands ofhours of manual work through automation and have gained
the insights they need to improve their batteries.

10

FEATURE ARTICLE“With NI’s SystemLink™ Software
as part of our architecture, we canbring our test data to all engineers
in a secure and easy way, thus
enabling them to view their dataand save templates for follow-up
tests, all in near real time.”
Ciro Spigno,
Group Manager, Battery Systems and Analytics Engineering,
General Motors

NI’s Modern Battery Validation
Lab: What’s the Novelty?
At NI, we have solutions installed at more than 80 OEMs andTier 1 suppliers, more than 20,000 battery test channels
installed worldwide, and decades of success automating test
tasks to accelerate time to market, reduce cost, and optimize
test operations.
The novelty of NI’s solution is that it drives value for state-ofthe-art labs as well as for those in need of a full overhaul.
Regardless of whether you need high-mix or large-scaletest, and independently from the existing infrastructure, NI’s
solution components and services are targeted at deliveringvalue where you need it, with minimum incremental costs.
We can work with you on a plan to modernize your battery lab
and deliver solutions that help you get to market faster andkeep your engineering resources focused on testing to makebetter batteries.

Author
Arturo Vargas Mercado
Chief Marketing Manager, EV Test, NI

Learn more

FEATURE ARTICLE

11

KEYNOTE
Industry Leaders Shed Light on How to
Use Test and Data to Increase Productand Operational Performance

THE VALIDATION TEST DATA WE GET FROM NI SYSTEMSENABLES OUR ENGINEERING TEAMS TO LEARN MOREABOUT OUR BATTERIES AND FIND WAYS TO IMPROVE
THEM EVEN AFTER THEY’RE IN THE FIELD.

-LARGE PARTNER PRESENCE
TRANSPORTATION RECAPPRODUCT INTRODUCTION
EV Battery Cycler Spans Wide Voltage Range
Modular design, high scalability serves
needs of battery validation labs.

BUILT TO SERVE BATTERY TEST LABS, THE HPS-17000
COMPLEMENTS NI’S PORTFOLIO OF BATTERY CYCLERS,OFFERING A SOLUTION THAT IS IDEAL FOR TESTING IN A
FAST-PACED ENVIRONMENT THAT NEEDS TO BE SCALED
AND EASILY SERVICED.
-EENEWS AUTOMOTIVEHENRIK RUDELIUS,
DIRECTOR, VALIDATION AND
SIMULATION BATTERY SYSTEMS, NORTHVOLTBetter Data Management
Starts Here
Collecting and analyzing the large amounts of data your team is collecting is a problem that may only be getting harder
to solve as testing requirements increase, timelines shorten, and talent and resources change roles over time.
VISUALIZATION

To help organize your thoughts about where to focus and prioritize your efforts, use the following questions to review yourcurrent implementation and how it might need to adapt and change to be maintainable, scalable, and actionable. As you
perform your self-evaluation, mark the column that most aligns with where you are and then set up a working session todecide with your team what the best path forward is for addressing the items that will have the biggest impact for you.

COLLECTING DATAGREATCOULD USE
IMPROVEMENTGREATCOULD USE
IMPROVEMENTNOT STARTEDGREAT

COULD USE
IMPROVEMENTNOT STARTEDGREAT

COULD USE
IMPROVEMENTNOT STARTEDDo all users have access to the visualization tool of your choice?
Is it easy to set user permissions to limit access to dashboards and results?
Can you easily make changes to align to any changes
in your testing and reporting needs?
NOT STARTEDCan you easily make an update to one or more data sources(i.e., deploy new software)?

Are your dashboards documented so that they scale with your test operations?

ANALYSIS

Do you have a process to consolidate data into a single location?
Are all of the analysis tools you are using compatible with each other?

Can you compare data across the product lifecycle
such as simulation vs. prototype results?

Can you assign user permissions to limit accessto certain analytics if necessary?

Will you be adding more test systems in the future
and will your existing process and tools scale?

DATA PREPARATION

Can you easily update an analysis routine and ensure version control?

GREAT

COULD USE
IMPROVEMENT

Are your analysis routines documented including a history of changes?
NOT STARTEDHow is the data saved and how easy is it to find and view a test result?

BUILDING A BETTER PRODUCTDoes all data you collect have metadata?

Are reports easily shared with key stakeholders?

Is the metadata consistent across all tests?

Can you easily share modified views with different departments?

Do you have an easy way to harmonize data that may have different units
or spellings (litre vs. liter)?

Do your current processes and deliverables support quick
and efficient action to be taken?

Do you have a way to harmonize data coming in from multiple labs,
facilities, or locations?

Do you document decisions and have a searchable archive?

Do you translate your data to a universal data model
to ease comparison of test results?

Can you perform a root cause analysis if an issue is identified
from your test results?

Is your process to prepare data documented so that you can scale your operations?
Is your process adaptable to quickly align with changing test
requirements or if you need to add additional test channels?
Do you have a way to connect to parametric data or test steps?

As you work with your team to prioritize efforts to improve your data collection, analytics, anddecision-making process, some questions to get the conversation started could be:






14

SELF-EVALUATION

What is your largest frustration with your existing data analytics and decision-making process?
How do you foresee your data needs changing in the near term? What about longer term?
How would leaving things the way they are affect your team/project now and in the future?
What would be the business value if you were to implement a better data analysis and decision-making routine?
What results could you achieve that you aren’t getting today?

SELF-EVALUATION

15

<AEB><Regular Algorithm><Highway Pilot><DNN Algorithm><10%

DATA UTILIZATION

Few Recorded
Scenarios

Open-Loop Testing

Closed-Loop
Testing∞ Simulated
Scenarios

Terabytes Of Data

Petabytes Of Data

>90%

DATA OVERHEAD

FIGURE 01
Comparison of a typical Level 2 assisted driving feature vs. a highly automated driving function.

Challenge

NI ADAS & AD Data Record Vehicle (left) and Jaguar Land RoverGround Truth Data Logging Car (right) at NI Connect Munich.

Safe like a Robot.
Drives like a Human.
Relax in your vehicle, while traveling long or short distances, totally avoiding any sort of congestionand preventing any collisions that lead to harm for traffic participant. This is the amazing futurethat autonomous mobility will bring to us. To make this a reality, you have to start from the very
foundation and build purpose into your brand DNA. This is what Jaguar Land Rover did andcontinues to do, by driving their reimagined strategy to fulfill their vison—creating the world’s
most desirable luxury vehicles, the best driving experience, and of course, new digital services.
16

CUSTOMER STORY

Develop and implement an open andflexible validation test strategy that covers
both the data needs and provides thetest coverage for neural-network-based
assisted and automated driving features
to enable modern luxury by design while
making mobility an even safer place.

Solution
Using the same common NI hardware
and software platform across Jaguar
Land Rover’s Verification and Validation
workflow to generate data from both
systems under test and from reference
systems has been a key to their success.
“My passion is in assisted and automateddriving, to make roads a safer place tobe. There are still too many accidents
happening. With assisted and automateddriving, we can help to reduce those. To
make the car behave like a robot but drive
like a human—this is, I think, one of the bestengineering tasks that you can think of,”says Joerg Schlinkheider, Chief Engineer

for Assisted and Automated Driving (AAD)
at Jaguar Land Rover. But to get there, we
still have to maneuver around a couple ofroadblocks. So, let’s drive right into this andexplore how the fine engineers at Jaguar
Land Rover are engaging in partnerships,
setting up their test strategy, and utilizing
data to bring forward the promise ofhighly automated driving together.

Data and Test Challenge
There are many challenges to put vehicles
out on the road, as they need to be safer
while at the same time utilizing higher
levels of automated driving. For example, alevel 2 feature like automated emergency
braking (AEB) can be found in manycars today. One of the key performanceindicators for an AEB function is false
activation. One of the main test methods isbased on replaying a finite set of recorded
scenarios in an open loop. The main
parameter to consider is the change of
distance between the ego vehicle and thetarget in front over time. This makes theamount of data still reasonable, and thetest complexity remains manageable.

But as we move toward higher levels of
automation, safety features become
more complex. Functions are now basedon neural networks and therefore they
do not only require thorough validation,
but they must be trained first. This meansthat an extra set of training artifacts has
to be created and then exercised by theneural network before the actual testing
can happen. In addition, features for highly
automated driving interact much more withthe ego vehicle. They not only take controlof the brakes, like in our AEB example, butthey also plan and steer the trajectory of
the ego vehicle. Hence, a tight closed-loop
validation approach becomes a necessity
and the number of scenarios for testing
converges towards infinity. As the amountof both simulated and recorded data at
Jaguar Land Rover is massive already,their clear focus is on maximizing theutilization of those datasets to further
optimize time, effort, and cost of test.

CUSTOMER STORY

17

Data and Test Strategy
It’s all about data. Data and data analytics have become the
new fuel for automotive products that Jaguar Land Roverdevelops and manufactures. The end-to-end relationships withmany other interfaces and systems around the vehicles are
increasing and are calling for an end-to-end validation strategy.
A very structured, layered, and data-driven approach is the
key that unlocks product potential and performance. A lot ofdata gets pushed into the cloud, where the teams at Jaguar
Land Rover are running data analytics, e.g., to understandin which situations or scenarios an interface has passed or
failed. They undergo a very rigorous systems engineering andvalidation design process; both the left and the right side of the
V-model have to be absolutely synchronized. Every requirement
has to be traceable to achieve the necessary robustness of
their products, which will then get released to customers.

Obviously, there is a strong focus on the early stages, utilizing
the shift left or front-loading strategy for design, development,
and test. Close collaboration between the validation engineers,
the systems engineers, and software architects is essential. The
well-known principle of system engineering also applies to agile
development. If you don’t specify and get your requirements
right in the beginning, it will be very costly in the end. To avoid this,every requirement needs to be traceable, as it is key for validationengineers to influence the model-based system design alreadyin the early stages. All the data that gets derived from test cars,
test rigs, or test assets are being pushed into the cloud to makedata-driven decisions. Essentially, this makes sure that the mostrobust safety features go along with new modern luxury as well.

Verification and Validation Test Strategy
100s

High
Proving GroundEngineering Fleet

Open Roadsst

Physical ECU +Simulated
Sensors

VIL

HIL

Model for
Other PDUs

HILModel for
Other PDUs

nd

Co

Physical ECU+ Sensors

Co

mp

lexi

ty a

Numberof Tests
Virtual ECU

SIL

PIL

Virtual MCU

MILRequirementsin the Loop

UNIT

Requirements +Models Review

1,000,000s

Low
FIGURE 02
Jaguar Land Rover’s Verification and Validation Test Strategy

18

CUSTOMER STORY

Joerg Schlinkheider,
Chief Engineer for Assisted and Automated Driving (AAD),
Jaguar Land RoverCustomer Fleet

Physical ECU +Simulated Sensors
Physical PDUs

Software Integration+ Configuration“NI is a company wework very closely
with. We see a
lot of really goodengineering thatfits to the way wewant to design our
products and tothe mindset that
we have in ourvalidation teams.”

Jaguar Land Rover and NI are
implementing this data and test strategy
together. Multiple, different testing
methodologies like lab-based testing using
software-in-the-loop (SIL), hardwarein-the-loop (HIL), and open-road testing
must be orchestrated in perfect harmony.
Using the same common NI hardware
and software platform to generate datafrom both systems under test and fromreference systems has been a key to thesuccess of Jaguar Land Rover. Using
XIL test environments like SIL, HIL, andvehicle-in-the-loop (VIL) make theirverification and validation (V&V) morerobust and efficient. This leads to better
quality overall—quality in V&V and qualityof the end product. The openness of the
NI toolchain allows Jaguar Land Roverto adjust the toolsets to their processes
and not the opposite. Furthermore,
Jaguar Land Rover is partnering with NIon joint future developments like AIbased scene detection. This will allow
them to identify interesting and relevant
scenarios, so they can quickly bringthem into their sophisticated validation
process. Converting these highly
relevant datasets to virtual scenarios toclose the loop will further enable themto test with scenarios driven by realworld situations, leading to lower costof data and higher data efficiency.

Partnerships
The Automotive industry has seen quite aparadigm shift in terms of future productcreation and delivery. The classic Tier 1 to
OEM relationship already feels like a fondmemory of the past. New technology andinfrastructure needs are both required
to either be the next innovation or to fuelthe next innovation. Jaguar Land Rover
believes in strong partnerships, andtherefore has joined forces with NVIDIA—apowerhouse in software, AI, and System on
Chip (SoC) development. Both engineering
teams are working closely together on awhite-box software collaboration to create
the next generation of driver assistancesystems and autonomous driving.
As mentioned before, Jaguar Land Roveris already collaborating deeply with NI
to put their test strategy into action.
One of the big pluses for Jaguar Land
Rover is that NI also works with manyother companies in different areas andindustries such as aviation and defense;
considerable knowledge and experiencecan also be transferred to Automotive
from these other domains. This is where
Jaguar Land Rover believes that they
can also learn from NI and its ecosystem
to achieve their robust, structured
approach to validation. Another importantpartnership that NI introduced to Jaguar
Land Rover is the connection to Seagate
Technology. Logging and storing data is
critical for Jaguar Land Rover’s groundtruth data systems. Seagate has expanded
their LYVE portfolio into rugged enterprise
grade high performance storage
combined with consumer ease of use,
data logistics, data operations, and manyother services. This again highlights a very
specialized area of expertise that only aglobal player and subject matter expert
like Seagate can address; therefore, they
are a perfect match for Jaguar Land
Rover within NI’s data logger solutions.

Nobody Is Perfect, but aTeam Can Be…
Jaguar Land Rover is on a continuous
improvement journey and to achieve
their reimagine vision with confidence,
the goal is to get the data coming in and,of course, pass all their test cases. Thiscan only be done by utilizing the powerof great teams—and Jaguar Land Roveris forming one of the best global teams
right now. They have been transforming
their business to agile, tearing down
silos and hierarchy. Engineers are now
empowered to lead and make decisions
from wherever they are in the world.
They are creating the new products
for an even safer future of mobility.
“At Jaguar Land Rover we are
reimagining our brands through thepower of our people, our partnerships,
our new data-driven products and ofcourse through cutting edge design.
And that means we need to recruit thebest people and we need to partnerwith the best,” says Schlinkheider.

AuthorDaniel Riedelbauch
Chief Solutions Marketing
Manager, ADAS & AD Test, NI

Watch the keynote

CUSTOMER STORY

19

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FIGURE 01
Northvolt’s battery manufacturing as a circular process that maximizes sustainability and drives them toward their goal of making the world’s greenest battery.

Making (and Testing) theWorld’s Greenest Battery
Northvolt’s mission is simple: make the world’s greenest battery. One of the most important
aspects of their operation is considering the battery production as a circular process, like a loop.
This “loop” goes from sourcing raw materials, through battery production, and to recycling so
the active material can be reused to make new batteries (Figure 01). As an example, Northvolt
aims at making 95 percent of cell material reusable after end-of-life, thus closing the loop
and restarting the process. This is critical to attain the sustainability goals that include lessdependency on “new” raw materials, more recycling, and cleaner batteries all around.
20

CUSTOMER STORY“The validation test
data we get from
NI systems enables
our engineering
teams to learn
more about ourbatteries and findways to improvethem even after
they’re in the field.”Henrik Rudelius,
Director, Validation and Simulation,
Battery Systems, Northvolt

This perspective of a circular process isapplied to Northvolt’s test strategy as well.
Their test engineers are challenged to “close
the loop” by using as much data as possible
to feed back into the manufacturing andtest processes. This data must be used todrive conclusions and actionable insightsthat help optimize and improve both theprocesses and the battery themselves.
Using this approach and data-driven
technologies, Northvolt can test
batteries beyond safety and quality,
to ensure they are sustainable,
traceable, and recyclable. Of course,
this approach comes with significant
challenges that we’ll explore further.

The Dot vs. the Comma
Northvolt uses a wide variety of equipment
and solutions that provide data that’s
potentially useful. With the variety,differences can be expected (shocking!).
One example of the different ways the data
is recorded is the decimal place, which
can be either noted as a dot or a comma.
While it is intuitively simple for engineers to
distinguish between 120.5 V and 120,5 V,
the data platform used by Northvolt needs
to automatically address that difference, so
the data can be correctly read, correlated,
and used to derive insights. Programming
this one behavior is not a hard thing to do,
but with thousands of battery cells andbattery systems deployed in the field, alongwith large-scale manufacturing and test
facilities, these differences add up andcan hinder a speedy test development
process by forcing engineers to do tasks
that don’t add significant value.

Challenge
Develop test systems that enable
Northvolt to “close the loop” in thebattery testing process, ensuring that
all available data can be proactively
used to improve upon the process aswell as the batteries themselves.

Solution
Leverage NI’s platform openness todevelop data-centric test systems
that empower Northvolt’s engineers toquickly find insights from data, adjust
their processes, and continuously
optimize battery performance.

CUSTOMER STORY

21

Even if all data from all sources came in the same format—which
it doesn’t—other challenges cause headaches for engineers.
Perhaps the biggest one is the lack of synchronization.
A lot of testing of Northvolt’s battery systems is done outside
the lab and around the world, after their batteries are deployed.
By getting the data of on-the-job batteries, Northvolt getsbetter insights on the batteries’ performance that help its
engineers understand and eventually improve them.
This data is automatically uploaded by the batteries’ telemetry
systems, through many wireless communication capabilities
like Wi-Fi, Bluetooth, or cellular. To minimize the effort ittakes to use the uploaded data, there are strict guidelines
to be followed on how it is recorded, time-stamped, sent tothe cloud, and made available for analysis. Doing this at thesource certainly saves time—but with limited engineering
time, there’s always room for improvement and time saving.
Moving on to the analysis side, after data is consistent, usable, andin the cloud, a productive interface is needed to get to actionableconclusions and insights. Capabilities like interactive plots,
flexibility to use Python scripts, and easy and intuitive filtering,are proving to be significant time-savers for Northvolt engineers.
And to further improve productivity, some analysis can be directly
performed in the cloud, thus saving time from downloadinglarge amounts of data. Let’s look at how this is achieved.

Connected Battery

NI Battery Data and Analytics Workflow

Northvolt has developed what they call the Connected Battery, asolution that involves capabilities for online telemetry, as previously
described, as well as for fleet management, local and remotediagnosis, and online software updates to their battery systems.

Situational AwarenessThrough this solution, Northvolt engineers can see and analyze
data at a very granular level. Variables like voltage, current,
temperature, state-of-charge, and state-of-health, are available
to be correlated, analyzed, and used to make fact-based
decisions. All of this happens on a secure, web-based interface
which also includes capabilities for one-click diagnostics, endof-life management, or warranty extensions, to name a few.

BATTERY ANALYTICSUSER DASHBOARDSCONFIGURABLE REPORTS

Systems Connectivity
DEVICE DISCOVERY

Through auto-synchronized and interactive plots, engineers canzoom into specific pieces of the data to drive conclusions andinsights about the battery. This enables them to continuously
make improvements and, in agreement with their customers, pushsoftware updates to the battery systems already deployed.

ADMIN TOOLS

Data Gateway

REMOTE EXECUTION

MONITORING AND TAGS

FILE INGESTION

Battery Validation Labs
Desktop
PC/Servers

NI Battery
Test System

Other Test
SystemTEST RESULTS

Benefits
Data Generating
AssetsThe development time required to come up with asolution like Northvolt’s Connected Battery is heavy, sosome limitations regarding scale are starting to surface,
driving their engineers to evaluate ways of achieving
scalability with minimum development overhead.

Reduce Cost of Battery
Development

100% Requirement
Compliance

Accelerate Productivity
and Time to Insights

Open and Interoperable
for Flexibility and Scale

FIGURE 03
NI’s data approach to battery test automates the end-to-end process to help engineers derive insights from test data and harness operational, economical, andtechnical benefits.

Product Development
Cylindrical or Prismatic

Cell Factory

Cell Data

Cylindrical or Prismatic

Packs and
Racks Data

Modules

Data Analysis and Feedback
for Product Optimization

Customer Products

Packs and Racks

Modules andPacks Data

Closing the Loop, Sustainably

Commitment to Test Data

Companies like Northvolt are extremely capable due to theirin-house capabilities and their continuous pursuit to improveupon their solutions. A critical requirement for any new solution
to evaluate is the openness to be compatible with Northvolt’s
existing equipment and proprietary protocols. Recently, they’ve
started to evaluate NI’s battery test solutions such as theBattery Test System, NHR Cyclers, and SystemLink™ software
to complement their capabilities with positive results:

At NI, we seek to elevate the role of test from a pass/fail process
to an enabler of product performance. We invest in EV test andlifecycle analytics solutions to enable battery manufacturers like
Northvolt to use test data to transform their businesses, achieve
their missions, and collectively drive the world to a greener future.

Connected Battery

Northcloud

FIGURE 02
Closing the loop at Northvolt drives test teams to effectively use all relevant data from product development and in-the-field batteries to feed back into their processes
and improve their products.

22

CUSTOMER STORYEngineering teams can quickly implement, change,
or customize functions to adapt test systems
to new battery products effectively.
System openness enables integration of existing assets andproprietary protocols to maximize reusability and speed up test.
SystemLink’s management of validation test data meets
their engineering teams’ expectations to learn more
about the batteries to find ways to improve them.

From this evaluation, it’s expected that Northvolt willcontinue to reduce cost of battery development, accelerate
their productivity, and comply with all requirements
necessary to make the world’s greenest battery.

Author
Arturo Vargas Mercado
Chief Marketing Manager, EV Test, NI

Watch the keynote

CUSTOMER STORY

23

NI Innovation Centersaround the GlobeAt NI, we work together with our customers to innovate solutions that ensure quality and shorten time to market
while assisting organizations in achieving their goals. NI’s Innovation Centers are essential for prioritizing thedemands of the client through promoting our industry-leading innovations.

Austin Innovation Labs
In February 2021, we introduced the NI Innovation Labs at our main campus in Austin, Texas. The state-of-the-art labs feature more than
32,000 square feet of dedicated space geared toward enabling our Systems and Product R&D teams to collaborate, innovate, and build
systems with our customers at the forefront of what they’re doing every day. The lab space is split amongst our business units yet configured
in such a way as to foster collaboration and allow our engineers to take advantage of advancements in innovation from any particularindustry. Our Transportation lab space consists of a few battery and high-power EV labs, an ADAS and Autonomy lab, a power conversion/
inverter lab, and an ECU test lab. With this facility, we continue to push the pace of innovation and help make our commitments to ourcustomers faster and more effective.

Michigan Innovation Center
China Innovation Center
In 2021, NI welcomed officials and representatives from the Chinese government, industry associations, key partners, and customers to join
us for the opening ceremony of NI’s China Innovation Center (CIC) located in our Shanghai office. The CIC is an important milestone in our
China journey to showcase what NI has to offer. Building upon this positive impact, we aim to become a leader in our targeted China markets
by keeping pace with innovation and next-generation technology development to be more competitive in global markets. Our presencein China is helping to deliver more value to local customers by shortening the iteration time to market and customer insights to solution
development and delivery.

24

HIGHLIGHT

In Spring 2023, NI is opening a Michigan Innovation Center in Novi, Michigan. This new facility will provide the latest technical and engineeringresources and will feature our ADAS/AD and EV demos for a variety of industries and applications. Our customers will be able to visit us andexperience the latest innovations for battery test solutions, cell quality, and ADAS/AD workflow in a live and immersive environment. Ourpresence in Michigan is yet another commitment NI is making for our customers in the Midwest region of the United States.

Tokyo Co-Engineering Lab
In July 2022, we opened Co-Engineering Lab in Tokyo, Japan. This lab space holds many of NI’s complex test systems with cutting-edge
technology. Over time it has become a place where test vendors, OEMs, Tier 1s, and tool vendors work together on innovative solutions andtry to solve their engineering challenges. Going beyond mere demonstration, our customers have a space where they can consult with ourexperts and collaborate on solving their most complex problems.

HIGHLIGHT

25

NI Replay and HIL System AD Specifications

Maximize Test Coverage with Your
ADAS/AD Replay and HIL Test System
Validating the perception, planning, andcontrol algorithms running on ADAS
electronic control units (ECUs) is key toensuring that ADAS and AD functions
are safe and reliable when they reachthe market. The industry needs toefficiently scale test coverage capacity byimplementing different test methodologies
such as Replay and Hardware-in-the-Loop,
which increases test coverage by moving
the bulk of testing from the road to the lab.
Testing complex algorithms on ECUs
requires replicating scenarios by injecting
real-world road data exactly as it was
acquired in the vehicle. Testing must also
expand coverage to include scenariosthat are extremely difficult or dangerous toencounter on the road. Simulation enables
you to create a nearly infinite number of edge
scenarios that will be required to ensure thesafe operation of ADAS and AD functions.

Replay Test Needs

01

01

Feed the system with external data inthe same way as it would be done withthe vehicle during actual test drives

Integrate hardware I/O withmultiple environmental simulationand modeling tools.​

HIL Test Needs

01
Stimulate the perception systems
with advanced processing anddata manipulation techniques toconvince the ECU that it is performinga real-world scenario.​

02
Integrate hardware I/O withmultiple environmental simulationand modeling tools.​

NI Replay and HIL ADAS and AD System: Advantage​








Ensure synchronous data feed fromeither your NI record systems or othertimestamped recording files.​Integrate simulation from modelingsoftware and inject signals fromdifferent sources for maximum
interoperability of test tools.​
Maximize test coverage by runningmore test cases and scenarios in lab
and simulation to decide which tests
must be performed on the road.​
Hardware and software
customization, flexibility,
and third-party openness
to future-proof your system.​

26

SOLUTION BRIEF

Common Test Needs







Develop faster by leveraging work
across design and validation throughNI’s toolchain to perform reliable test
at each stage.​
Keep requirements from outgrowing
your test capability with NI’s range of
I/O for cameras, radar, V2X, lidar, and
GNSS sensors and buses.​A unified test system architecture
to move back and forth between
data replay and HIL test with thesame system and single platform fordata record.

02
Maintain adaptability for future I/O
and test requirements as systems
continue to add more cameras, radar,lidar, and other ADAS sensor types.​

Environmental Server
Host Interface
Test
Results

PXI Real-Time Controller
Storage (OS)Camera1
CAN, LIN, FlexRay

Test
Sequencing

Automotive Ethernet

Real-Time
Processor

Scene andEnvironment
Modeling
SoftwareReplay and HIL
AD Application
SoftwareGPU
HIL
Data Cache for
Pre-Recorded
Data orEnvironmental
Simulation

RDMA

ReplayData Parsing
and Retrieval
SoftwareLoad and
Sensor Sim

Ethernet 2
High Bandwidth
In-System Data
Movement3
10 MHzSync Clock

Timing & Synchronization
FPGA Co-Processor
Internal Storage
RAID Controller

Signal Conditioning and Fault Injection

Increase Test Efficiency by Unifying Replay and HIL Test into One System ​ECU

Vehicle Model
Scenario
Model

HIL
Components

Increase test coverage reliability
and repeatability through direct
injection techniques to insert
faults, frame delays, and more
into the sensor bitstream.​

ReplayComponents

1

GMSL, FPD-LINK, FPGA-BASED

2

1 GBIT TO 50 GBIT

3

PCI EXPRESS BUS

Replay and HIL AD softwarefor data throughput, timing andsynchronization, direct interface
with ECU, full customization, datarepositories, and simulation interfaces.

02

RDMA

Storage for Data Replay / Test Results (Recorded Data)or Cloud Location

03

01

PXI technology provides hardware
and software faulting capabilities—
down to nanosecond synchronizationand timing control for reliable
execution of test cases.

03“AD and ADAS require the combination of different
test methodologies which is challenging but essential
to provide driver and passenger safety and ultimately
for AVs to become a reality. With NI solutions, we
can build up systems and move one step closer to acomprehensive test strategy consisting of both realworld and virtual test efforts.”
Dr. Thomas Herpel,
Senior Manager, ZF Mobility Solutions

Modular hardware generates signals toemulate ADAS sensors interfaces, vehicle
bus traffic, and general purpose I/O totest sensor fusion on the ADAS controller.

04
Hardware integration openness
to interface with Hexagon (Vires),
Applied Intuition, IPG, Ansys,
aiMotive and more simulation, andmodeling software providers.

05
Open software-centric approach
to interface and source data fromIT infrastructure and cloud service
providers like Microsoft Azure,
AWS, Seagate, and more.

System Integration on Your Terms
NI offers a variety of solution integration options customized to your application-specific requirements. You can use your own internal
integration terms for full system control or leverage the expertise of our worldwide network of NI Partners to obtain a turnkey system.
To learn how you can increase product quality and shorten test timelines, contact your account manager or NI at (888) 280-7645 or
info@ni.com
ni.com/transportation

SOLUTON BRIEF

27

Closing a Critical Coverage Gap
in ADAS/AD Camera Validation

OPTICAL LAYERLENSLOGICAL LAYER

Photo DiodeArray

Image Sensor

Vision Component<Video Source><Video Sink>

Digital Image

Digital Image

For car manufacturers and suppliers, validation and homologationof such systems present a new class of challenges. From
conventional quality assurance methods, only testing is effectively
applicable to NN-based ADAS ECUs. A lot of investments are
made in the testing phase before start of vehicle production. One
popular approach due to economic and reproducibility reasons isfunctional testing in a lab-based environment, clustering relevant
ECUs in a hardware-in-the-loop (HIL) setup while the rest of thevehicle bus is simulated. The sensor stimulus is then injected into
the ECUs on a digital path.

LENS

These and other safeguards are employed to make sure that
autonomous vehicles can yield control to the driver quickly to
avoid following a ghost trajectory due to faults in the image path.
Simply injecting a video stream or a previous recording into an
ECU will, thus, trigger the failsafe mechanism.

Image Sensor

Video Component

Host Processor

CAN/ETH<Video Source><Video Sink><ADAS Controller><Vehicle Comm>

Captures and sends
image data
Receive backchannel
communication

Converts video
stream to object list
(neural network based)

Receives object list
and applies rules
to detected objects

Send backchannel
communication

Run ADAS functions(LKA, AEB, TSR, etc.)

FIGURE 01
Typical Architecture of an ADAS Camera System (Simplified)

Exposure
Control

MIPI CSI2
Packetizer

ADAS ECUs responsible for safety critical vehicle functions are
required to self-diagnose faults and relinquish control of thevehicle in a safe manner (failsafe). For a vision ECU, that means
observing the operational status of the image sensor(s) andvalidating the provided video stream in real time.
Modern image sensors provide multiple ways of securing the data
paths to and from the downstream video processor against errors:
Some manufacturers enable CRC checksums on the side-channeltransactions. The video stream can be configured to include alive
counters and configuration state snapshots in the image. Somesensors include an ERROR interrupt output pin. The MIPI CSI2
specification additionally provisions for CRC guards and frame
counters on the protocol level.

Communicates tothe rest of the vehiclearchitecture

WHITE PAPER

NN
Classifier

Temperature
Sensor

PLL

StatusMonitoring

MIPI CSI2
Depacketizer

PHY

PHY

I 2C
Register File

I 2CController

DIGITAL LAYERFIGURE 02
Simplified View into an Image Sensor and a Downstream Vision Component

This challenge has been known from day one and the obvious
remedy was to turn off ECU software health monitoring andstatus validation altogether. This is better known as “HIL-mode”
for vision ECUs which is also supported by Mobileye and othervendors like Bosch or Continental. While this is a valid mechanism
to enable perception layer and application software testing, theinherent downside of this approach is that the software release
under test is not the software that will be deployed in the field later.
Therefore, validation tests miss parts of the test coverage, which
are only present in the production software.
One solution here is to reverse engineer and emulate the image
sensor’s behavior in real time to enable production-release ECU
software testing.
Figure 02 depicts a simplified conceptual model of an image
sensor acting as the video source and a connected visioncomponent as the video sink. At the logical level, digital images
are produced in the image sensor and consumed by thevision component.
Each incoming image is analyzed before being forwarded to theperception layer. Specific image properties, such as the average

28

Image Analysis
and Processing

ADC AND
PROCESSING

Testing production release software for camera-based advanced driver assistance systems is difficult
due to the integrated safeguards for meeting functional safety requirements. To satisfy the validity
checks of the device under test and stimulate behaviors similar to test driving, NI provides dedicatedhardware and software for emulating image sensor functionality on three different layers, helping to
avoid the need for a dedicated testing mode software build for validation (known as HIL-mode).
Vision-based Advanced Driver Assistance Systems (ADAS) are an
integral part of modern vehicles and supplement the vehicle’s viewof the world in the visible electromagnetic spectrum. They provide
important autonomy functions, improving road safety throughautomated vehicle trajectory planning based on object detection
and classification. At the core of many ADAS Electronic Control
Units (ECUs) lies an ASIC accelerating Neural Network (NN)inference on sensory input. Mobileye Global, Inc., provides one of
the most widely used chipsets for these NN-based subsystems.

PERCEPTION LAYER

brightness, histogram, etc., are fed to a control module responsible
for tuning the image sensor to produce properly exposed images
suitable for object classification.
Status monitoring will extract alive counters and validate thesensor’s configuration state by extracting information fromembedded data within the image. This is the module that makes
it difficult to provide any generic video stream to the ECU in a
HIL environment without using pre-release software including
ECU “HIL-mode.”
An injection system needs to emulate the behavior of multiple
sensor sub-components in real time to avoid triggering failsafe
measures in the vision component and produce reliable test
results for detection performance.
Simulation of the optical layer is the domain of the host computer
generating the sensor input data. In open-loop regression tests,
a previous recording from a similar camera ECU is replayed to
the DUT. Generating live synthetic data using a visualization tool
enables closed-loop tests for scenario exploration, functional,
and performance testing. The quality of the generated data
is directly linked to the fidelity of the optical sensor model.

WHITE PAPER

29

Simulation

Data Preprocessing

Data
Movement

Data and Fault Injection

DUT
LENS

1

Image Sensor

2

5

CSI2

PC with GPU

4

6

7

Simulation
Software1

8

Decoding Interface

RoCE2,
HDMI

Input Decoding,
Preprocessing

Histogram,
Metadata Gen

EMULATE LOGICAL LAYER

Automotive Camera Interface
Fault Injection,
Digital Emulation

PEER-TOPEER PCIE(PXIE)

Synchronization,
SerDes Output

EMULATE LOGICAL LAYERGMSL,
FPD-LINK

I2C

Custom Interface

BACKCHANNEL,
COMM (I2C)

CSI2

I2C

Camera ECU

DIRECT INJECTION SUBSYSTEM FOR SENSOR DATA

3

1

2

Special Transmission
Coefficients of Lens Coatings

Vignetting

3

4

Lens Distortion and Aberrations

Depth-of-Field

5

6

Spectral Transmission
Coefficients of Photo-Diode
Color Filter Array

7

Conversion Efficiency/Sensitivity

8

Noise Modelling (Poisson vs.
Gaussian, ADC Non-Linearity)
1

Exposure Time Emulation

Interoperable with third-party software

2

RDMA over Converged Ethernet

FIGURE 04
NI HIL System Architecture for Direct Data Injection Using Production Release ECU Software

FIGURE 03
Effects on the Opto-Electrical Path

The optical properties that are usually covered, to varying
degrees, in a synthetic simulation are shown in Figure 03.
On the logical layer, the bulk of emulation efforts will usually bedominated by on-line digital image manipulation. Some visionsystems might have the sensor dynamically crop the image andplace the readout window across the active pixel array. Sensors withcolor filters provide individual color channel amplification for whitebalance tuning in varying lighting environments.
The intensity of the incident light may sometimes exceed thecapacity of the photodiodes to capture the whole dynamic
range of the scene, especially at night. To increase the captured
dynamic range, modern sensors allow for multiple analog-to-digitalconversions during the exposure time. Each individual conversion
yields 12 bits of brightness information that is then internally stacked
to a final 20-bit digital image. To save bandwidth, the 20-bit image
can then be compressed to 12 bit or 16 bit using a dynamicallyconfigurable, non-linear transfer function.

30

WHITE PAPER

Downstream processors may depend on image statistics provided
by the sensor to correctly control the exposure time. Image
sensors can generate dynamically configurable histograms with
the image output.
The digital layer is shaped by low-level protocol and electricalparameters. While these also dictate the PCB design for the
ECU interface, the relevant configuration parameters internal
to the sensor include online configuration of the MIPI CSI-2
communication module and the clock rates generated by thePhase-Lock Loop (PLL), ultimately driving the output frame rate.
Additionally, sensible outputs from the Register File need to beprovided (e.g., temperature sensor and status flags readout).
Real-time embedded systems have tight design timing
constraints (latency and throughput) that need to be respected
when building instrumentation interfaces. In addition toemulating the image sensor functionally, great care must be
employed to react to requests and provide data streams
within the timing constraints of the target device under test.

NI’s solutions portfolio covers all the aforementioned topics
providing modular and customizable testing systems for ADAS/ADECUs (see Figure 04).
Leveraging a strong partner network, NI can provide customized
instrumentation interfaces for all but the most tightly integrated ECUs.
The real-time core of the image sensor emulation IP is realized on a
dedicated high-performance scalable hardware platform capable ofsupplying multiple UHD video streams in parallel, covering the needs
for modern vehicle vision systems. In addition, the emulation core iscapable of deliberately inserting faults into various processing stages
to enable test coverage of the error handling mechanisms in the DUT.
On the simulation side, NI hardware provides scalability and openness
to third-party software simulations that can be connected to theloop via a bi-directional high bandwidth RDMA over Converged
Ethernet data link. Compatibility with optional third-party simulation
tools is given by adapting HDMI data sources.
In summary, ADAS ECUs, being safety-critical systems, use statusmonitoring safeguards that make video injection a non-trivial task.
A sophisticated, multi-layered, real-time image sensor emulation
model must be used to satisfy the validity checks in the ECU andto generate video streams that elicit behavior from the perception
layer similar to real-world test driving.
NI’s sophisticated optical simulation and real-time emulation forimage sensors allows for comprehensive verification of current andfuture vision based ADAS/AD ECUs worldwide. NI solutions enablevalidation tests based on production software for vision ECUs, whichcloses a coverage gap that has existed since the introduction of“HIL-mode” using pre-release software.

Author and Co-Author
Dimitrij Gester
Senior Offering Application Expert, ADAS Simulation, NI

Daniel Riedelbauch
Chief Solutions Marketing Manager, ADAS & AD Test, NI

WHITE PAPER

31

HPS-17000: 150 kW SiC-Based Power for EV Battery Test at Scale

Specifications

Flexible and Scalable EV Battery Cycler
The need to quickly increase EV battery
testing capacity is making validation labs
harder to manage and forcing engineering
teams to explore ways to sustainably
scale up their test lab operations.
From few to dozens of test cells,
managing power from the battery
cyclers is one of the main challenges
that impacts lab efficiency, CO2
footprint, and operational expenses.
A software- and data-centric test
strategy can help but requires flexible
test equipment that can be synchronized,
orchestrated, and operated effectively.
Battery cycler flexibility and openness
is critical to achieve the scale neededin modern battery validation labs.

HPS-17000: Advantage​








Layout Flexibility: Microsecond
synchronization with timesensitive networking enables
parallel operation of cyclers
regardless of location in the lab.
​ pplication Coverage: In addition toAbattery cycling, its sub-ms dynamic
performance makes it suitable forbattery test, inverter testing, anddynamometer applications.
Easier maintenance: Individual
SiC-based power modules(PMSiC) can be replaced andstocked for higher uptime.
Standardization: Power- andapplication-specific breakout sectionsin the cabinet support lowering thecost of service across applications.

32

SOLUTON BRIEF

Customer Needs

NI HPS-17000

01

01

Test existing 400 V and 800 V EV
battery architectures, and future-proofing
for higher voltage and test capacity needs

150 kW battery cycler with low- and highvoltage modes of operation, up to 1500 V

02
Define battery validation lab layoutsthat work for current and future needs

03
Maximize lab equipment utilizationand integrate existing equipment

04
Monitor and manage full lab operation
to optimize operational cost

02

OUTPUT POWER, MAX±150 kWRATED SUPPLY VOLTAGE

480 V rms, 3-PHASE DELTA(NO NEUTRAL)

400 V rms, 3-PHASE DELTA(NO NEUTRAL)RATED INPUT CURRENT,FULL-LOAD AMPERES

230 A

270 A

RATED FREQUENCY

60 Hz

50 Hz – 60 Hz

SHORT-CIRCUIT CURRENTRATING SCCR (UL)

25 kA rms SYMMETRICAL @480 V MAX

Parallel cycler operation without physicalproximity, providing flexibility to lab layout

03
High maintainability with modular
design and swappable power bricks

04
NI’s software-connected approach
to automate configuration, execution,and reporting on test operations

OUTPUT VOLTAGE, MAX

OUTPUT CURRENT, MAX

DIMENSIONS(L X W X H)

WEIGHT

750 V DC (HIGH CURRENT MODE)
1500 V DC (HIGH VOLTAGE MODE)+/- 480 A (HIGH CURRENT MODE)+/- 240 A (HIGH VOLTAGE MODE)

925.2 mm X 1408 mm X 2123.6 mm(36.4 in X 55.4 in X 83.6 in)

1650 kg (3638 lb) – CYCLER ONLY1830 kg (4035 lb) – CYCLER WITH CRATE

System Integration
on Your Terms
NI offers a variety of solution integration
options customized to your applicationspecific requirements. You can use yourown internal integration terms for fullsystem control or leverage the expertiseof our worldwide network of NI Partners to
obtain a turnkey system.
To learn how you can increase productquality and shorten test timelines,
contact your account manager or NI at(888) 280-7645 or
info@ni.com
ni.com/transportation

COOLINGFORCED AIR
900.0 mm (35.4 in) MIN CLEARANCE FRONT AND BACKSOLUTON BRIEF

33

Mobility Solutions
for a Better
Tomorrow
In the last few years, we have experienced significant changes
and new challenges for the automotive industry, facing
shifts in technology with the introduction of electric andautonomous vehicles.
Today more than ever, it is clear that the traditional approach
to automotive tests can no longer deliver the technical insightand business performance to solve dynamic problems. In bothautonomy and electrification, software defines the performanceof the system, creating incredible adaptability to evolve andimprove as engineering teams learn more about their designs.
Companies with a software approach,such as China Euro Vehicle Technology(CEVT), are disrupting the businessby applying new approaches to thedesign, validation, and test phases
by using data and simulation andinvesting in toolchains that can scale
and adapt to new technologies.
CEVT is the European R&D andinnovation center for ZEEKR, a
Zhejiang Geely Holding Group Co. Ltd.
company. It is based in Gothenburg,
Sweden, and has the mission to be at
the forefront of new developments inthe world of mobility, striving to achievea different and better tomorrow.
Established in 2013, the businessbegan with the mission ofsetting a revolutionary vehiclearchitecture, CMA, designed withfull scalability to accommodate awide range of propulsion systems
and technology solutions.

CEVT has since evolved to becomea world-leading, core hub for mobility
innovation, taking ownership ofa broad range of projects andregistering hundreds of proprietary
inventions per year. In that time, thebusiness has expanded from eight
employees to incorporating some
1,700 personnel in Gothenburg.
With the mobility industry evolving
rapidly, the concept of personaltransportation is also transforming, withnew ways of thinking about the vehicle asa product. CEVT is leveraging its worldleading expertise and agility to pursue
exciting mobility innovations, helping topower the shift towards electrificationand craft a different, better future.

CEVT headquarters: Uni3 building at Lindholmen, Gothenburg

34

CUSTOMER STORY

Meeting the Demands of Tomorrow

At the Forefront of Mobility Solutions

Being a relatively new team in the automotive business inthis era comes with several advantages, as it allows you tothink outside the box and innovate to find a world of new
possibilities to serve the industry’s demands faster.
This is the case of the Vehicle Hardware-in-the-Loop(HIL) Systems team at CEVT formed by HIL engineers
with experience working with different vendors. The
team is led by Bengt Augustsson, who has an IT andsoftware engineering background, which helped to bring a

Subsystem

different mindset to solve test challenges innovatively andefficiently than what would be traditionally expected.
HIL is a test methodology well-established in automotive
validation. Vehicle systems are increasingly using complex
electronic, intelligent, and interconnected systems toprovide advanced safety and comfort features to vehicle
occupants. It is more important than ever to be capable ofperforming and scaling from subsystems’ component level tomultidomain HIL systems for full vehicle integration tests.

SystemMulti-Domain

The success in this area relies on the ability to seamlessly integrate
toolchains, test cases, and models into one system. NI’s modular
hardware and open software make this integration possible. The
PXI platform allows engineers to extend current test capabilities
with a wide range of modules to meet different system integration
testing needs as new ECUs are added to the system. VeriStandsupports the inclusion of new and existing models in an HIL test
system. Compliance with standards such as ASAM, AUTOSAR,
and FMI ensure that customers can incorporate additional
suppliers’ offerings in the future as requirements change.
Selecting a modular, open platform allows hardware andsoftware to be reused as testing scales from component
level to system level to full vehicle system testing.

Transitioning from system-level to multidomain simulationis achieved through the NI and ALIARO components andintegration approach. The xMove master rack with a controller
allows you to integrate across multiple domains and is based on
Switch Load and Signal Conditioning (SLSC) modules with multipurpose I/O channels. In particular, the reconfigurable AL-1010
Multifunction SLSC plus the xMove Configurator Software are
key as allows engineers to deploy new I/O allocations maps
in minutes, as each physical pin can switch between different
signal types through the software, therefore reducing thetime and cost between tests, projects and programs.

xMove Master RackxMove Subsystem Chassis
NI SLSC
Verify the function of a collectionof components, such as the complete
seat (motors, heating, weight sensor, etc.).

Initial Requirements and Specifications Provided
All they knew was that they needed a full test system that could
perform the test as soon as possible—well before having accessto the physical components, one that was capable of adapting
quickly to unknown requirements across projects and time.

Simulate the environment of automotive components asrealistically as possible. They can have up to 200 different
types of car components that need to be tested within thesystem, where a third part of the components normallyalso contained software elements. Without having accessto the product, the team must ensure the software andhardware pieces will work together as designed.
Based on the requirements list and project scope, they started
looking for an open, flexible software-based solution that couldchange, grow, and adapt along with their customers’ requirements.

DUT

Mass Interconnect

Project Scope

Deployed
ModelsTest Stand

Communication
Buses

FIGURE 01
Scaling from Subsystem to Multidomain HIL

Six years ago, when the team started to define the projectframework, they discovered the traditional solutions for vehicle
tests are static systems that have a lot of dependencies
on deliveries from different suppliers creating a bottleneck
across the process. As the team goal and focus relied on
shifting to the left in the validation process to provide data
and results faster to their suppliers and customers, theydecided to look outside the “traditional” turnkey solutions
for new possibilities by developing a solution innovatively.

Host PC

NI EtherCAT

Verify the function of two systems together,such as a seat and infotainment system. Testing is focusedsystem integration, not single component function.
Fault Insertion

Verify function of a single component,such as a seat motor.

NI PXI

Load
Simulation
Sensor
Simulation

SignalConditioning

Analog
In/OutxMove
Configurator

Real-Time
Processor

VeriStand UIVeriStand RT
EngineHost Interface

FPGA
DigitalIn/OutPower Distribution

Power Supply

External Loads

FIGURE 02
NI + ALIARO xMove HIL Test System Architecture

36

CUSTOMER STORYCUSTOMER STORY

37

Hardware Change

System HIL with Three
Subsystem Units and One PXIRemove One Subsystem Unit to Enablea Separate Subsystem HIL and a System
HIL with Three Subsystems

Subsystem HIL withOne Subsystem Unit and One PXISoftware Change

System HIL with Preconfigured System
Definition File and Running VeriStand on
PXI Controller

System HIL with Preconfigured System
Definition File with Reduced I/O and
Running VeriStand on PXI Controller

System HIL with Preconfigured
System Definition File for Running
Subsystem HIL and Running
VeriStand on PXI Controller

FIGURE 03
Subsystem to Multidomain HIL for Future Expansions

Similarly, system definition files can be merged as new
vehicle domains and racks are introduced into the system,
providing excellent flexibility and extensibility of thesystem for many years to come, simplifying test setup.

Driving the Shift Toward
Tomorrow’s Mobility
By working with NI Partner ALIARO as the prime supplier for the
integration of a solution that can match a multi-vendor environment,
the HIL team was able to find problems early in the design process,before even having a prototype vehicle for testing. This enabled
their engineers to save valuable time, reduce operational costs
associated with addressing the identified issues, and avoid potential
costly recalls for bugs otherwise not found by conventional testing.
This helped CEVT to successfully integrate multidomain
HIL testing into their validation process with the flexibility
and adaptability they needed to test quickly—evenconsidering the unknowns on the projects’ specifications.
A main goal for the project was to build one system that can serve
across different project with different configurations at the sametime without to restart everything each time. The NI + ALIARO
open turnkey solution provided complete control to the HILteam to upgrade and adapt the solution over time. They still
maintain the same hardware configuration and components
as when they started. Most of the updates and time have been
focused on the software configurations to adapt and meet the
specifications of the different projects that have come throughthe team. Also, their systems are fully automated with remote
access, which allows them to serve projects across the globe.

38

CUSTOMER STORY“By using NI’s PXI and VeriStand
platform as the core of our HIL
system and ALIARO knowledge
and expertise to provide turnkey
flexible and adaptable solution wewere able to build a Vehicle HIL
system that meets and adapts
across time to our different vehicle
programs. The way our HIL
rack is configured gives us theconfidence that we will be using
it for a long time, by integrating
software updates to serve the rapid
automotive industry changes.”
Bengt Augustsson,
HIL Team Leader, CEVTFIGURE 04
CEVT Multidomain HIL Rack Systems

Across the different test teams within CEVT, Bengt Augustsson’sgroup is normally the first option stakeholders reach out toin order to perform the early tests. Because they are fasterto respond, they can quickly adapt to the new needs andspecifications through software and provide a complete reportand overview of how the complete vehicle HIL product will
look like.
The impact and contribution from the team to CEVT is huge
and a well-known success inside the company and among theircustomers. This one flexible HIL rig has facilitated software
validation of several platforms and numerous car programs
throughout the years. By having a HIL system that can serve
different cars’ projects with their own uniqueness on theirconfigurations and across ranges, stakeholders can also comeand look at the deliveries and gain access to the systems
and the data.
As a technology supplier, we are proud of what the CEVT teamhas built together, by incorporating different ways of thinking
and problem-solving capabilities. But as they like to call it, there
is always a world of possibilities to keep improving. The CEVTHIL team is looking forward to keeping impacting positively

by providing innovative solutions along with the right partners
and ecosystems and interconnected and integrated solutions
capable of adapting quickly to serve the mobility industry.

Interviewed People:
Bengt Augustsson,
HIL Team Leader, CEVT

Jonas Axelsson
HIL Architecture Design and Maintenance Engineer, CEVT

AuthorBrenda Vargas
Senior Solutions Marketing Manager, ADAS & AD Test, NI

CUSTOMER STORY

39

The Dos and Don’ts of Working
the Data and Software
Connected Workflow

The Enterprise-Level Challenge“Hi, my name is Dan, and I am a Chief Field Application Engineer at NI. I have been working in theEngineering domain since 2005—so more than 17 years—covering ADAS and Autonomous Driving(AD) related topics for about 5 years. In my role I get to work closely with our customers in the
Automotive industry and in particular with major global OEMs. With this series of articles, I would liketo share my insights and experiences that I have gathered so others can apply best practices andavoid pitfalls through lessons learned. Well, let’s get moving, as the future of autonomous mobility
will not be waiting for us.”With simple setups like a single camera and a single radar, you might
be dealing with roughly 70 MB/s (1.3 megapixel, 12-bit grey scale,
36 frames/sec.). An entire 8-hour drive will fit on a 2 TB USB thumbdrive. At the end of the day, you could pull the thumb drive, visualize
data locally on your standard laptop at “real time“ speeds, thenduplicate the thumb drive overnight, put the thumb drive copy in an
envelope, and mail it back to your V&V lab to use that data as partof your validation process. Guess what? We have talked to multiple
OEMs that were still using this approach as of 2022!

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WHITE PAPER

Storing, finding, sharing, and using data in a way that scales has
always been a challenge for organizations. The scale around AD ishaving an exponential effect.
The scale of data in an AD system is exploding. Systems are goingfrom the standard of one or two cameras and a single radar to 20
cameras (multiple forward-facing ADAS cameras, 360° surroundview, electronic mirrors, driver monitoring systems, etc.) and fiveradars as the new normal for level 3 automation and above. Even
though this is common knowledge, it is very hard to fully understandhow far-reaching the ramifications are.

The next generation of autonomous cars requires around 5 GB/s.
Let that sink in. 70 MB/s became 5 GB/s, in one generation. And
we are already hearing people talking about up to eight and even
10 GB/s! A continuous eight-hour drive nowadays requires 144 TB of
storage capacity (5 GB/s × 3600 s/hr × 8 hrs). That doesn’t fit on asingle SSD of your standard laptop—let alone a USB thumb drive.
Manually backing up the data becomes impractical, so RAID-basedstorage systems become a requirement. This effectively “doubles”
the required hard drive space. These two factors result in multiple
SSDs that can no longer be mailed but must be shipped. Insteadof leaving an envelope at the hotel front desk, the driver has to planstops to a parcel service every day. But still, this is about as far as
people see today, and we believe these ramifications are still justsmall ones. So, let’s dig a level deeper.
Most company-issued laptops have SSDs that are somewhat
limited at about 3 GB/s read/write speeds. Gigabit internet can pusha theoretical maximum of 125 MB/s. Typical software applications
tend to cap out around 4 GB of memory and even fully 64-bit
systems typically come with 8 GB of physical memory. At 70 MB/s,
the current generation data stays nicely under all of these limits.

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41

Data Searchand Visualization

REAL DATAFAULT REPRODUCTIONDYNAMIC DATACONFIGURATIONSREAL DATADATA INGESTIONSYNTHETIC AND RECALCULATED DATAREAL DATAREAL DATASYNTHETIC AND RECALCULATED DATASYNTHETIC AND RECALCULATED DATA

AD organizations are rapidly expanding in head count. OEMs
and Tier 1 suppliers are restructuring their workforce. The
shift from areas focused on internal combustion towards
vehicle electrification, automated driving, and simply softwaredevelopment in general is visible everywhere. We have witnessed
OEM organizations putting orders of 1,000+ engineers on AD
feature development as a starting point. Some businesses areeven going further, both in terms of sheer volume as well as carving
out this massive amount of engineers and putting them into aseparate, start-up-like organization. One way or another, all thoseusers want access to the massive data described above. But how
do you handle getting 1,000+ people data that can’t be used on
their standard laptop, to people distributed around the globe andliterally “working from anywhere” including their homes? How doyou effectively scale not only with the data, but also with the users?

The End-to-End AD Validation Workand Data Flow

Another huge shift is in ownership. The current generation of
ADAS ECUs is completely owned by the Tier 1 supplier. They own
the IP, the perception integration, the ECU hardware, the validation
tools, the visualization tools, the data loggers—simply speaking,they own it all. The OEM pays for all of it but keeps none of it. It is

42

WHITE PAPER

Cloud/
On-Prem Storage

REAL DATA

basically a subscription model. When the OEM changes suppliers,
all the infrastructure and tools leave with them. To avoid this, we
see OEMs bringing the next generation of technology in house.
The classical model of the Tier 1 supplier feeding its technology
into the OEM is shifting, but many of them are starting, mostly,from scratch.

Figure 01 shows how the data is used throughout the organization.
Data originates in road testing (upper left) and gets ingested
into cloud storage (center). From there, users search the data tovisualize it (top), build data sets, and start analysis (bottom). They
move into simulation and the synthetic world for iterative testing(bottom left) and eventually get to hardware with open-loop andclosed-loop testing (right). At each stage, new data is generated
and put back into the central cloud storage, the data lake. We will
cover each of these areas in greater detail, touching on specificlessons learned from customer conversations.

Simulation and
Digital Twinning

ALGORITHM ITERATIONDESIGN DATAFAULT REPRODUCTION

Data can be streamed from disk, over a network, or buffered inmemory. At 5 GB/sec, data can’t be loaded from disk in “real time”(more like .5x speed), streamed over a network in “real time” (.025x
speed), or buffered for more than a second in memory. In short,the customer’s laptop and overall workflow went from effective touseless trying to utilize raw data—again, in just one generation!

Closed Loop Testing

DESIGN DATARoad Testing

Data Management,
Analysis, and Reporting

Open Loop/
Replay Testing

FIGURE 01
The End-to-End Validation AD Work and Data Flow

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43

Deployment Release

Capture and Monitor

A lot of the data originates from recordings done in the field—orfrom the road, to be precise. Let’s start here and follow the data
lifecycle throughout the validation process. There are two distinct
approaches in use for ADAS data logging. The first approach uses
an external logger installed in the vehicle. The second approach
uses the internal AD ECU to record and upload events.

D e p l oy

S e r vi c e s

D eve l o p

Dat a

DesignOpenness
Reuse
Scalability
Future-Proof

Te s tIntegration and Testing

Simulation

Deployment Release

End of Line

Data

Data and Test Management

Capture and Monitor

ADAS/AD Data RecordSensor Production TestAsset and Fleet Management

StorageECU Production Test

Data Visualization and Analysis

Smart Triggering

Regression TestingTest Coverage and Analysis

Pre-Labeling

Data Compression and Annotation



Platform Reuse

Hardware-in-the-Loop Farm

Integration and Testing

Replay/Hardware-in-the-Loop

Services

Engineering and Consulting

Simulation

Software-in-the-Loop

Injection Techniques

Methodology Consulting

Physics-Based Sensor Models



Fault Injection



System IntegrationEnvironment Simulation



Third-Party Simulation

Certified Solution Delivery Partners



Simulation at Scale

Testability Studies



Third-Party (Open Interfaces)

Hardware V&VEndurance, TemperatureCharacterization

FIGURE 02
The NI Solution Portfolio Enabling the Data- and Software-Connected ADAS/AD Workflow

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WHITE PAPER

Road Testing and Data Logging

When looking at external data loggers, there are a couple ofkey specs that these need to fulfill. The obvious ones are data
throughput, tight synchronization of all data streams, and saving
every single bit without any loss to a large enough storage device.
In addition, the data recorder needs to be modular and flexible
in both hardware and software architecture to adapt to any
changes. Having a path to expand for future sensor sets is of highimportance. Companies trying to take on AD responsibilities
directly are typically starting with a low variant (fewer cameras)
but will quickly be following on with the full system setup. Similarly,
if future vehicle architectures go beyond 5 GB/s, you want to beprepared and not locked into an architecture or solution that will
not allow you to keep up the pace, or only doing so by purchasing
a completely new data logging system.
NI provides high-end, high-throughput logging that can handle
12 camera setups like Mobileye’s SuperVision or Nvidia’s DRIVE
Hyperion. Again, these vehicles are pushing 5 GB/s. Getting thedata in a time synchronized way, from acquisition hardware to
backplane to hard drive is clearly one of our strengths. Even if
more data throughput is required, it is just a matter of adding more
systems, staying synchronized, and scaling. Physical space andpower requirements will be the only real limiters for a multi-systemsetup when it comes down to sheer throughput. External loggers
need to make sure that all of the data streams are going to besynchronized and timestamped accordingly, so that later on ina replay scenario the data can be injected into the ECU in a timesynchronous fashion.

tagging and labeling. Lastly, we will investigate internal dataloggers (ECUs) and start to compare the pros and cons of both
approaches to close out road testing as a whole.
This concludes the first article on best practices and lessons
learned implementing the data and software connected
workflow. Dan will continue to share his insights within the next
issues of the Automotive Journal. This is just the very beginningof the AD data and software workflow. It is NI’s goal to enableorganizations through a set of software and hardware solutions
to help complete this complex puzzle (Figure 02). NI aims to makesure its customers and partners can accelerate development
and turn test into a strategic advantage that will unlock greater
product performance.

Author and Co-Author
Daniel Eaton
Chief Field Application Engineer, Transportation, NI

Daniel Riedelbauch
Chief Solutions Marketing Manager, ADAS & AD Test, NI

Only this way you can guarantee the perception algorithm on the
ECU will get its data for cameras, radars, and lidars at the exact
right timing to then draw the right conclusion; for example, is thisobject a vulnerable road user, a car, truck, where is it currently andwhere is it moving to, and so forth. The NI-based solution comeswith built-in timing and synchronization capabilities, which allows
users to synchronize interfaces, channels, and data streams down
to the microsecond level. Furthermore, various timing and sync
mechanisms and sources can be used, such as GPS, IEEE 1588,
gPTP network synchronization, and many more.
So, we covered data throughput and synchronization today.
Next time we will continue with the third obvious spec, which isstorage. Again, it is about throughput and most importantly about
write speeds. But there is more than meets the eye here, too.
Afterward, we will check out additional parameters like modularityand flexibility to adapt to changes for external loggers and data
reduction including compression and triggering, as well as data

WHITE PAPER

45

NI Connect
Austin, Texas

MAY
23–24

NI Connect will focus on technology innovations that continue toredefine product and operational performance and how we’re
working with innovators like YOU. Join fellow engineers and leadersof industry who are passionate about accelerating the developmentof innovative technology that performs flawlessly. Register here.

Vehicle Electronics Connected Services
Gothenburg, Sweden

NI Recognized for Innovationin the Automotive Industry
During the recent Battery Innovation Center (BIC) annual industry
luncheon, NI was the recipient of the Charged for Innovation award
which recognizes a company with fielded technology whose magnitude
is amplifying and sustaining the automotive industry. NI was honored
to be recognized amongst industry peers by one of the nation’s leading
battery research initiatives. Our team, along with BIC, continues to push
the envelope of testing to enable automotive companies to develop safeand reliable energy storage systems. Special thank you to the team at
BIC for the recognition, and for hosting NI at your annual luncheon.

46

EVENTS

2023 Event Schedule

MAY
23–24

MAY
23–25

MAY
24–26

Vehicle Electronics and Connected Services in Gothenburg is
all about the autonomous and electric future of transportation.
Meet with us there to talk about the complete ADAS
workflow—from Record to Replay and HIL. More info.

The Battery Show Europe
Stuttgart, Germany
The Battery Show Europe brings together experts from all domains
around battery testing. NI will show how our battery test approach helps
customers scale up battery production. More info.

Automotive Engineering Exposition
Yokohama, JapanThe largest exposition in Japan for automotive engineers and the opportunity
to discover the latest technologies and products. Meet NI experts totalk about Battery Test and complete ADAS workflow. More info.

Automotive Testing Expo Europe
Stuttgart, Germany

JUNE
13–15

JULY
5–7

Automotive Testing Expo is the world’s leading international expo forevery aspect of automotive testing. Meet our experts to talk about
everything automotive, from testing and validating various ECUs to thelatest news in ADAS/AD, Battery Test, and Electric Drive Test. More info.

Automotive Engineering Exposition
Nagoya, JapanThe largest exposition in Japan for automotive engineers and the opportunity
to discover the latest technologies and products. Meet NI experts totalk about Battery Test and complete ADAS workflow. More info.

EVENTS

47

Learn More

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