bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Method for Secure Odometer in Automotive Systems
Authors: Ansari Asadullah , P.C. Karthik , D H Sharath , Devarasu Dhanasekaran
Published: April 2023

Vehicular odometers serve as a standard component in driver assistance system to provide continuous navigation. Odometer fraud is the disconnection, resetting, or alteration of a vehicle’s odometer with the intent to change the number of miles indicated. Odometer fraud occurs when the seller of a vehicle falsely represents the actual mileage of a vehicle to the buyer. But the Odometer readings are essential when it comes to ascertaining the fair market value of a used vehicle. Hence, there is a need to protect the odometer which resides in the instrument cluster of the digital cockpit. Any manipulation is very difficult to detect and to prove once made, even by expert technicians using specific On-Board Diagnostics (OBD) testing devices. One of the most critical issues is that currently odometers are not locked out from external access, in contrast to other vehicle components, which have higher protection levels. As a result, odometers are not sufficiently cyber-secured and there is a need to identify one – or more – technical solutions that would prevent their tampering. In this regard, a secure odometer solution is proposed here, which is deployed on a tamper proof hardware module with security features that are not available in the core processor in any Electronic Control Units (ECUs) to execute the proposed secure odometer solution. The secure tamper proof hardware is an add-on module to any vehicular processors for providing secure environment compared to conventional Hardware Security Modules (HSMs). The secure storage is stored a zero miles/kms value during the manufacturing by provisioning either in the trusted execution environment or the secure tamper proof hardware. The calculated distance from the odometer is added cumulatively into the secure storage distance under a fixed certain frequency. During each vehicle boot, the odometer error is calculated between the displayed distance and the distance stored in the secure storage like Replay Protected Memory Block (RPMB). If the error exceeds the fixed threshold, then displayed distance is updated with the previously stored secure storage distance as a correction mechanism. Hence, odometer corruption is prevented.
Protection of Firewall Rules Using Secure Storage for the Infotainment System
Authors: Pacharla Sreedhar Reddy , Prasad Pavan Kumar , Vimlendra Suryansh , Varshney Saurav , Tiwari Vishal
Published: April 2023

A modern car is enhancing the driver’s in-vehicle experience through the infotainment system which is a combination of both information and entertainment. The Original Equipment Manufacturers (OEM) are being driven to provide this luxurious experience through the development and adaptation of new technology. In a luxurious car, an infotainment system consists of a high-resolution touchscreen display, smartphone pairing, support for multimedia, installed applications for entertainment, etc. The applications responsible for this experience will exchange the data from the Electronic Control Unit (ECU) to the server and vice versa. If all applications require a unique port for the exchange, then the number of ports will be more which means the number of entry points to exploit the system by an intruder will be increased. For the secure exchange of information, the ECU software consists of a firewall that monitors this exchange and allows only the safe transfer of data to avoid the compromise of the system. A firewall blocks unwanted traffic and data from unauthorized resources. Linux system establishes the firewall through the iptables which has rules to filter ipv4 and ipv6 packets. But these rules are in the root file system which can be accessed directly. If there is no monitoring system for these tables, an intruder can change the rules which leads to an entire system compromise. The proposal is to place the rules in secure storage which is difficult to access by an intruder. This concept makes use of ARM TrustZone technology and requires an implementation of a trusted application running in a secure world through which secure storage can be accessed. In this paper, a comparison of the time taken to enforce the rules between the default process and the proposed process is shown.
Consequence-Driven Cybersecurity for High-Power Electric Vehicle Charging Infrastructure
Authors: Carlson Barney , Rohde Kenneth , Crepeau Matthew , Salinas Sean , Medam Anudeep , Cook Stacey
Published: April 2023

Cybersecurity of high-power charging infrastructure for electric vehicles (EVs) is critical to the safety, reliability, and consumer confidence in this publicly accessible technology. Cybersecurity vulnerabilities in high-power EV charging infrastructure may also present risks to broader transportation and energy-infrastructure systems. This paper details a methodology used to analyze and prioritize high-consequence events that could result from cybersecurity sabotage to high-power charging infrastructure. The highest prioritized events are evaluated under laboratory conditions for the severity of impact and the complexity of cybersecurity manipulation. Mitigation solutions and strategies are presented to secure the vulnerabilities that potentially lead to high-consequence events. These mitigations can be immediately implemented by industry or executed during the design stage.
Shared Autonomous Vehicle Mobility for a Transportation Underserved City
Authors: Meneses Cime Karina , Guvenc Levent , Aksun Guvenc Bilin
Published: April 2023

This paper proposes the use of an on-demand, ride hailed and ride-Shared Autonomous Vehicle (SAV) service as a feasible solution to serve the mobility needs of a small city where fixed route, circulator type public transportation may be too expensive to operate. The presented work builds upon our earlier work that modeled the city of Marysville, Ohio as an example of such a city, with realistic traffic behavior, and trip requests. A simple SAV dispatcher is implemented to model the behavior of the proposed on-demand mobility service. The goal of the service is to optimally distribute SAVs along the network to allocate passengers and shared rides. The pickup and drop-off locations are strategically placed along the network to provide mobility from affordable housing, which are also transit deserts, to locations corresponding to jobs and other opportunities. The study is carried out by varying the behaviors of the SAV driving system from cautious to aggressive along with the size of the SAV fleet and analyzing their corresponding performance. It is found that the size of the network and behavior of AV driving system behavior results in an optimal number of SAVs after which increasing the number of SAVs does not improve overall mobility. For the Marysville network, which is a 9 mile by 8 mile network, this happens at the mark of a fleet of 8 deployed SAVs. The results show that the introduction of the proposed SAV service with a simple optimal shared scheme can provide access to services and jobs to hundreds of people in a small sized city.
On-Road Real-Time Hyper-Local Air Quality Monitoring Based on Mobile IoT Enabled by a Network of Vehicles Equipped with Air Quality Sensors
Authors: Jung Heejung , Borrel Herve , Taddonio Paolo
Published: April 2023

People are exposed to disproportionately high concentrations of air pollutants daily on and near the road during their ride, walk, and residency. Currently air quality monitoring is performed mostly at background locations far away from the road and distinctive point, line, and area emission sources, failing to report concentrations on the road. This study presents an innovative air quality monitoring method using a network of vehicles equipped with air quality sensors (AQSs). Vehicles are connected to internet through either cell link or apps used by drivers. A cloud server collects the data and updates air quality concentration maps every 10 minutes. The study presents very high temporal and spatial resolution maps at a fraction of the cost of previous studies. These high spatiotemporal resolution air quality maps can be used to reduce public exposure in many ways including but not limited to cabin air flap door control, eco-driving route for navigation, and daily exposure monitoring. The method has a potential to be deployed worldwide.
An Analysis of Data Curation Techniques throughout the Perception Development Pipeline
Authors: Perrin Jacob , Hasenklever Daniel
Published: April 2023

The development of perception functions for tomorrow’s automated vehicles is driven by enormous amounts of data: often exceeding a gigabyte per second and reaching into the terabytes per hour. Data is typically gathered by a fleet of dozens of mule vehicles which multiply the data generated into the hundreds of petabytes per year. Traditional methods for fueling data-driven development would record every bit of every second of a data logging drive on solid-state drives located on a PC in the vehicle. Recorded data must then be exported from these drives using an upload station which pushes to the data lake after arriving back at the garage.

This paper considers different techniques for curating logged data. These curation methods are performed to maximize the usefulness of the data throughout its lifecycle and minimize the amount of data necessary for perception development and validation The reduction of logged data has the effect of not only curtailing storage costs, but also minimizing latency for data availability and maximizing possible campaign drive time. Advanced techniques considered include: (a) the real-time evaluation of sensor and bus signals, (b) the application of artificial intelligence (e.g. for similarity-based image discovery and dynamic scene content detection), and (c) using function prototyping to inform the data curation process. In addition, various possible integration points for the curation techniques are considered in the data ingestion pipeline - from the cloud in the datacenter to the in-vehicle logging system on the edge. The trade-offs for each proposed techniques are considered across the various components of the data ingestion pipeline to explore the feasibility of - and to arrive at some conclusions for - designing more intelligent data collection campaigns.
Anti-Skid System for Ice-Snow Curve Road Surface Based on Visual Recognition and Vehicle Dynamics
Authors: Pang Chenghui , Zhu Haotian , Lin Zhenmao
Published: April 2023

Preventing skidding is essential for studying the safety of driving in curves. However, the adhesion of the vehicle during the driving process on the wet and slippery road will be significantly reduced, resulting in lateral slippage due to the low adhesion coefficient of the road surface, the speed exceeding the turning critical, and the turning radius being too small when passing through the corner. Therefore, to reduce the incidence of traffic accidents of passenger cars driving in curves on rainy and snowy days and achieve the purpose of planning safe driving speed, this paper proposes a curve active safety system based on a deep learning algorithm and vehicle dynamics model. First,we a convolutional neural network (CNN) model is constructed to extract and judge the characteristics of snow and ice adhesion on roads. By training the residual network, the road surface can be identified and classified under 7 different weather conditions, and the adhesion coefficient of the road surface at this time can be obtained. In addition, the magic formula is used to establish a tire curve driving dynamics model and combined with the curve radius and other parameters to solve the safety speed threshold in the curve driving process. Finally, MATLAB and CarSim software are used to build a simulation platform for verification, and real vehicle experiments verify that the system has strong reliability and robustness. The research shows that the prediction accuracy of the training set and verification set of the system reaches 93.7% and 85.93% respectively. Compared with the traditional back propagation (BP) neural network method, the recognition accuracy of the road adhesion coefficient is improved by 4.53%. Therefore, the recognition algorithm combined with road surface parameter information in this paper has higher prediction accuracy and robustness, which can significantly improve the safety of vehicle driving on curves on rainy and snowy days.
A Unified Frequency Understanding of Image Corruptions and its Application to Autonomous Driving
Authors: Zhang Zhuang , Zhang Lijun , Meng Dejian , Tian Wei , Xiao Wei
Published: April 2023

Image corruptions due to noise, blur, contrast change, etc., could lead to a significant performance decline of Deep Neural Networks (DNN), which poses a potential threat to DNN-based autonomous vehicles. Previous works attempted to explain corruption from a Fourier perspective. By comparing the absolute Fourier spectrum difference between corrupted images and clean images in the RGB color space, they regard the noise from some corruptions (Gaussian noise, defocus blur, etc.) as concentrating on the high-frequency components while others (contrast, fog, etc.) concentrate on the low-frequency components. In this work, we present a new perspective that unifies corruptions as noise from high frequency and thus propose an image augmentation algorithm to achieve a more robust performance against common corruptions. First, we notice the 1/fα statistical rule of the natural image's spectrum and the channels-wise differential sensitivity on the YCbCr color space of the Human Visual System. Thus we present a new perspective of the relative Fourier spectrum in the YCbCr color space which unifies the noise from all 15 common corruptions as noise concentrating on the high-frequency components. From the new perspective, the SOTA (state-of-the-art) image augmentation algorithm shows insufficient coverage of frequency change compared with common corruptions and an insufficient improvement in robustness against perturbations on the frequency domain. Second, based on the unified understanding of image corruptions and limitations of the SOTA image augmentation algorithm, we present a frequency-based image augmentation that adds noise to the high-frequency components in the YCbCr color space with the amplitude of noise proportional to the spectrum amplitude of the image. Compared with previous works, the proposed method achieves SOTA performance against corruptions on common datasets (CIFAR-10 and tiny-ImageNet) and real-world driving tests.
Development of Measurement Capability in Cylinder Head Combustion Chamber Volume
Authors: Reddy Basudeb
Published: April 2023

The Indian Ministry of Road Transport and Highways (MoRTH) issued a notification of Bharat Stage (BS) VI emission standards for all major on-road vehicle categories in India directly, skipping BS V. In BS VI emission norms and performance of two wheeler engine, its very important to control the engine parameters. Hence some stringent tolerance applied to the engine parts dimensional specification. One of the main part of the engine is Cyl. head, in which combustion chamber is one of the critical parameter. Cyl. head combustion chamber volume plays critical role for emission norms and performance of engine and it should be measured accurately. Current industry practice for cyl. head combustion chamber volume inspection method with help of liquid filling inside the chamber. This method has got some limitation for achieving R&R less than or equal to 10% due to many uncertainties are included. If not measured close to specification in inspection process, then it will lead to low engine performance and also may lead to violating the emission norms. This paper discuses about new learning on critical parameter i.e cyl. head combustion chamber volume inspection with scanning technology non-contact dimensional inspection method to capture cloud co-ordinate points. These cloud co-ordinate points further used for computing the free form area of the chamber for volume calculation. This method also satisfying in line with MSA AIAG 4th edition guideline to achieve R&R less than or equal to 10%. Which will support to avoid unreasonable risks due to variation in cyl. head combustion chamber volume caused by malfunctioning of two wheeler engine motorcycle performance. Key concepts of item definition, combustion volume, determination of MSA & R&R and emission concept will be presented.
A Study on Flexible Transparent Electrode Materials for Touch Sensor
Authors: Kweon Kyoungchun , Hong Seungchan
Published: April 2023

As the AVN display in the car interior becomes larger and located above the center fascia, the driver's visual visibility is becoming important. In addition, since an expensive touch sensor is installed, a transparent electrode cost reduction technology for a display touch sensor that can replace an indium material, which is an expensive rare metal, is required. In this paper, we developed new transparent electrode materials and manufacturing methods for the touch sensor film which light reflectance is low and flexible without a separate low-reflection multi-layer, so that the design freedom is high and the material cost is low. By optimizing the amount of fluorine doping ratio in tin oxide, excellent electrical conductivity and high optical transmittance are secured, and the surface reflectance is reduced by adjusting the diameter and length of the silver nanowire. As a result, it was shown that the AVN display image and font readability was improved. In addition, we verified that the material has probability to adoption to a curved and flexible display applications for future mobility based on autonomous driving.
The Influence of the Material Construction of Leatherette in Squeak Noise Control
Authors: Palaniappan Elavarasan , Mohammed Riyazuddin , Lewis Edlin , Balaji K V
Published: April 2023

PVC (polyvinylchloride) synthetic leather or called leatherette is being widely used for automotive interior applications for seat cover, gear boot, gap hider, steering wheel and roof liner due to their leather like feel and texture, flexibility, sewability, affordability, and wide design freedom. However, the leatherette construction such as top coating, backing fabric and fabric weaving pattern plays a critical role in the finished leatherette performance for the specific application. This study provides the influence of different coating material and different backing fabric in squeak behavior of gear boot PVC leatherette. The squeak behavior was studied by stick slip test as per automotive engineering requirements, and the response of these coating and fabric surface was measured in the form of Risk Priority Number (RPN).
A High Strength Aluminum Solution for Polymer Coated Bearings
Authors: Campbell Sylvia , Stearns John , Morais Paulo
Published: April 2023

Aluminum-tin (Al-Sn) and aluminum-tin-silicon (Al-Sn-Si) alloy lined bimetals have traditionally been utilized in rod and main bearing applications in light duty gasoline engines due to their combination of strength and soft-phase properties, such as embeddability and conformabilty. The load carrying capability of Al-Sn-Si alloys can be further increased by applying a polymer overlay, but recent advances in engine design, to improve efficiency and reduce CO2 emissions, have resulted in maximum specific load requirements beyond the performance limits of current Al-Sn-Si-Cu products. In these instances, the usual option would be to specify a lead-free bronze-based bearing solution, which has increased strength, but necessitates greater weight and brings a significant cost disadvantage over aluminum products. To address these problems, we have developed a novel high strength aluminum lined bimetal for use with a polymer coating, which offers a significant advantage in load carrying capability over traditional Al-Sn-Si-Cu alloys. The novel high strength developed alloy employs an Al-Mn-Mg substrate, which is roll bonded to a steel backing. Bearing rig testing has demonstrated a significant improvement in fatigue performance over the highest rated Al-Sn-Si bearing alloy and an acceptable level of seizure and wear performance. Initial particle tolerance test results are encouraging. A 900-hour thermal shock engine test established the potential of the development alloy to perform satisfactorily in an application which typically uses a more costly bronze-based bearing solution.
Effect of Pre-Strain and Baking Temperature on Bake-Hardening Behaviour of BH220 Steel
Authors: Jain Vikas , Misal Swapnali , Paliwal Lokesh , Sathaye Asmita
Published: April 2023

Light weighting has been one of major driver in automotive industry for few decades. Today when automobile industry is in the transition from internal combustion engine to electric vehicles it becomes even more dominant driver. Many high strength or advanced high strength steels are used in different parts of automotive body for down-gauging and light weighting. BH 220 steel is used in automotive skin panels for its bake hardening property. BH220 provides excellent combination of formability during stamping process and dent resistance in skin panel parts post painting and baking cycle. This material uses CED oven temperature for baking and provide bake hardening effect (BH effect/BH Index) in parts due to increase in yield strength by 35-70 MPa. Current national and international standards specify requirement on BH Index at 170°C for 20 minutes with 2% pre-strain. In order to optimize paint shop CED oven baking temperature, study carried out to know baking temperature effect on BH Index at different pre-strain. In this study effect of baking temperature & %pre-strain on BH Index is studied. For Bake hardening study, tensile samples are prepared, pre-strained to 0, 0.5,1 and 2 % and subjected to bake hardening at different temperature in 130-170°C range for 20 minutes. Tensile testing is performed to evaluate BH Index for these samples. Based on study empirical relation is generated, that can provide BH Index on different baking temperature. The result shows increase in BH Index with same pre-strain however rate of increment is less post 150°C baking temperature. Additionally, BH Index reduces with increase in pre-strain with same baking temperature.
Topological Data Analysis for Navigation in Unstructured Environments
Authors: Mollan Calahan , Pandey Vijitashwa , Pinapala Amith
Published: April 2023

Autonomous vehicle navigation, both global and local, makes use of large amounts of multifactorial data from onboard sensors, prior information, and simulations to safely navigate a chosen terrain. Additionally, as each mission has a unique set of requirements, operational environment and vehicle capabilities, any fixed formulation for the cost associated with these attributes is sub-optimal across different missions. Much work has been done in the literature on finding the optimal cost definition and subsequent mission pathing given sufficient measurements of the preference over the mission factors. However, obtaining these measurements can be an arduous and computationally expensive task. Furthermore, the algorithms that utilize this large amount of multifactorial data themselves are time consuming and expensive. Often, it is valuable to make assessments about a terrain with limited information and using similarity with existing terrains without necessarily performing the entire simulation. This paper will investigate how topological data analysis (TDA) can be used to describe ontological features of the collected terrain data and how those features can be used to help navigation of the mission without making assumptions of the mission requirements or operator preferences.
Methodology to Arrive at Passing Criteria of Plastic Parts Subjected to Vibration Fatigue
Authors: Jawahar Nagarjun
Published: April 2023

In research and development of any automotive industry the main challenge is to virtually simulate probable failures rather than relying on physical testing which consumes time and resources. It is even more challenging when it comes to failure prediction of ABS plastic parts due to its complexity in material, behavior and assembly variations. ABS material is used extensively in automotive vehicles especially in motorcycles and scooters due to its visual and structural benefits at moderate cost. In this paper, the work showcases a methodology to predict failure of ABS parts. In order to do so, understanding the shortcomings in the current system is necessary. With the help of testing database history of various vehicles on proving grounds, root causes and drawback with respect to current simulation process are identified for failure of ABS parts. The input excitations from proving ground are probabilistic, thus, random vibration fatigue process is then introduced to calculate life. By correlating the simulation predicted life with testing, the required factor of safety to include residual stresses, assembly stresses are calculated and passing limit in terms of stress is derived for ABS parts to further reduce the simulation run time. Using six sigma methods, the accuracy in simulation is improved with which cycle time, prototype cost and testing time is reduced.
Verification of Driver Status Monitoring Camera Position Using Virtual Knowledge-Based Engineering
Authors: Alonso Liliana , Lopez Rubio David , Lopez Diego , Rodrigez Wendolyne , Arroyo Alejandro
Published: April 2023

A DMS (Driver Monitoring System) is one of the most important safety features that assist in the monitoring functions and alert drivers when distraction or drowsiness is detected. The system is based in a DSMC (Driver Status Monitoring Camera) mounted in the vehicle's dash, which has a predefined set of operational requirements that must be fulfilled to guarantee the correct operation of the system. These conditions represent a trade space analysis challenge for each vehicle since both the DSMC and the underlying vehicle’s requirements must be satisfied. Relying upon the camera’s manufacturer evaluation for every iteration of the vehicle’s design has proven to be time-consuming, resources-intensive, and ineffective from the decision-making standpoint.

This work describes the methodology followed to leverage the Virtual Knowledge-Based Engineering to improve flexibility and expedite the decision-making process, while ensuring the main operational ranges of the system are satisfied for the system’s design trade space in question.
Optimization of Aluminum Sleeve Design for the tow eye Durability Using DFSS Approach
Authors: Fahir Ahamed , Choudhari Satish , Michalowski Krzysztof
Published: April 2023

The automotive industry is moving towards larger SUVs and also electrification is a need to meet the carbon neutrality target. As a result, we see an increase in overall gross vehicle weight (GVW), with the additional weight coming from the HV battery pack, electric powertrain, and other electrical systems. Tow-eye is an essential component that is provided with every vehicle to use for towing during an emergency vehicle breakdown. The tow-eye is usually connected to the retainer/sleeve available in the bumper system and towed using the recovery vehicle or other car with towing provision. Therefore, the tow-eye should meet the functional targets under standard operating conditions. This study is mainly for cars with bumper and tow-eye sleeves made of aluminum which is used in the most recent development of vehicles for weight-saving opportunities. Tow-eye systems in aluminum bumpers are designed to avoid any bending or buckling of the sleeve during towing for whatever the GVW loads. So that the vehicle doesn’t face any tow-eye system failure, which would prevent another car from towing the breakdown vehicle and would need special roadside assistance to take it for servicing. This paper uses the Design For Six Sigma (Taguchi Method) approach to identify the potential control factors (from the benchmarking study) to optimize the tow-eye sleeve to withstand higher GVW load without functional loss.

Furthermore, this approach proved that the selected optimum design is less sensitive to noise factors such as aluminum property variation, bumper beam thickness variation, and load direction variation. The learnings from this paper will help to reduce the development time and cost by implementing the robust sleeve design in the early stage of the program.
Developing Equipment Condition Prediction and Monitoring System Using Deep Learning Models in Automotive Production Factory
Authors: Kim Deog Hyeon
Published: April 2023

A technology was developed to recognize and predict the urgent degradation of the state of the rotating equipment installed in Hyundai-Kia factories. It is also being applied to activities to prevent equipment failures by establishing a monitoring system using this technology. Vibration data and artificial intelligence (AI) algorithms were used to predict conditions. It was developed and installed so that maintenance engineers could predict failures in advance. This is to improve preventive diagnosis of thousands of rotating equipment in the factory. And it has the advantage of allowing a small number of engineers to monitor exponentially increasing number of equipment. Vibration data including trends and alarms were collected along with the production schedule, and wavelet-based preprocessing DB9 (Daubechies 9) was performed to remove noise such as outliers. Two different AI algorithm models were developed to recognize and predict changes in equipment state. First, 1D-CNN (Convolutional Neural Network) was used as a model for initially recognizing rapid changes in vibration trend. The reliability of the model was evaluated by converting the difference between the inference result and the actual result data into numerical values based on the probability distribution. Second, a future vibration trend prediction within 7 days was developed by combining LSTM (Long-Short-Term Memory) and 1D-CNN algorithms. LSTM is well known for predicting time series data. The reliability of both models is demonstrated by RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error, %). Each model of MAPE is 99.9% and 99.3%, respectively. Monitoring of equipment states has been established with two models that secured reliability, and rotating equipment at the factory are currently managed.
Study of Newly Improved Material Solution for Inverter Application
Authors: Hyun Soon-Young , Kim Haekown , Ryu Suil , Baek Namjoong
Published: April 2023

Previous material solution for industrial inverter applications was PC/ABS for more than 10 years. Recently, PC/ABS has been reduced in the market due to customer needs for improved performance of existing materials and market trends for improved material like raising carbon credits are emphasizing the need for eco-friendly environmental technologies and rapidly growing smart factories to deliver, smart power consumption technologies for environmental protection and energy saving. This trend is rapidly changing in common life and various industries, so new material solutions are required to improve effective material solutions such as less or no outgassing, thermal stability and lower process temperature availability, color stability, better flame retardant properties and so on. In this study, according to new industry requirements, material evaluation was conducted with SABIC NORYLTM N-series PPE resins and incumbent PC/ABS material. Through various experiments, we confirmed the excellence of N1050 which can be processed at a lower temperature as 260~275°C injection molding process with less outgassing, fewer flow mark and gate mark and weld line. Better flowability for each processing temperature and MFR and flammable retardant properties and thermal analysis through TGA are also checked, so the thermal stability of N1050 is identified superior properties for the inverter application comparing to incumbent material.
Assessing Enterprise Level, Augmented Reality Solutions for Electronics Manufacturing
Authors: Becerra Elijah James , Hovanski Yuri , Tenny Joe , Peterson Rebecca
Published: April 2023

With the growth of Industry 4.0 in recent years, Augmented Reality (AR) technologies are changing the way operators work by increasing their efficiency and operational performance. A common use of AR is providing operators helpful work instructions for assembly by presenting relevant digital information in the context of the physical environment. These AR experiences can be viewed via several devices such as mobile, wearable, and stationary devices, each being useful for different applications. While in the experience, instructions are provided by means of 3D animation, text, images, and interactive buttons, all of which are directly overlaid onto the physical product or equipment being worked on. This work presents a closed-loop, enterprise connected, AR system for post end Printed Circuit Board (PCB) assembly work instructions. The system is designed to work with a stationary device, allows for varying types of PCB”s, provides overlaid instruction, and logs important information to an enterprise system, such as overall cycle time, step cycle time, number of errors, type of error, and who performed the assembly. A comparison was made for single cell manual assembly PCB work instructions using both an Industry 4.0 driven system and a more traditional manufacturing system which used packets, tracers, Manufacturing Execution System (MES), and PDF instructions. Discovered benefits of an enterprise connected AR system included increased throughput and utilization, improved communication between operators and support, reduced overtime costs, reduced defects, reduced non-value-added secondary inspections, nearly 50% increase in ergonomics, reduced labor due to rework, and improved corrective actions due to granularity between steps compared to total operation. This AR driven solution transformed the single cell manual assembly to be more informed, make better decisions, and help operator productivity.
Access Control Requirements for Autonomous Robotic Fleets
Authors: Tusing Nathan , Brooks Richard
Published: April 2023

Access control enforces security policies for controlling critical resources. For V2X (Vehicle to Everything) autonomous military vehicle fleets, network middleware systems such as ROS (Robotic Operating System) expose system resources through networked publisher/subscriber and client/server paradigms. Without proper access control, these systems are vulnerable to attacks from compromised network nodes, which may perform data poisoning attacks, flood packets on a network, or attempt to gain lateral control of other resources. Access control for robotic middleware systems has been investigated in both ROS1 and ROS2. Still, these implementations do not have mechanisms for evaluating a policy's consistency and completeness or writing expressive policies for distributed fleets. We explore an RBAC (Role-Based Access Control) mechanism layered onto ROS environments that uses local permission caches with precomputed truth tables for fast policy evaluation. To demonstrate the features, we will compare policy outputs against SROS (Secure ROS) policies and test our approach against simulated malicious adversaries with penetration testing and fuzzing techniques.
Development of Novel Steering Scenarios for an 8X8 Scaled Electric Combat Vehicle
Authors: Kim Junwoo , El-Gindy Moustafa , El-Sayegh Zeinab
Published: April 2023

This work investigates the steering and wheel speed control of a completely custom built 8x8 scaled electric combat vehicle (SECV) which has been constructed to meet the Ackermann condition at low speeds. During remote control operation the scaled vehicle is capable of continuously maintaining and varying the individual wheel speed and individual wheel steering angles of all eight wheels in real time. Several steering scenarios have been developed including traditional (front 2-axle steering), fixed third axle (first, second and fourth axle steering), all wheel steering and crab steering (all wheels are parallel with same steering angle). The traditional, two axle steering scenario is experimentally tested for accuracy in this work with planned future research for experimental analysis of the other steering configurations.

This work is conducted using Arduino software to control the physical SECV and TruckSim software to simulate the dynamics of the vehicle. The results obtained from the physical testing of the wheel angular velocity were validated using a handheld tachometer device. The steering angle measurement of each wheel was validated using linear actuator sensors. It was seen that the physical results from the SECV are within acceptable range of the theoretical data calculated and simulated in Trucksim Software. The continuous steering method is applied by investigating the relationship between the steering angles of all eight wheels while operating the steering system from zero to the maximum steering angle of the 1st axle inner wheel during a turn. A major contribution of this work is a novel physical experimentation of the continuous Ackermann relationship for eight wheels. During testing of the traditional two-axle steering configuration the metrics of performance that were reviewed include: wheel speed, center velocity, yaw rate, and eight-wheel steering angles. With these metrics being compared with the Trucksim simulation, the experimental results obtained from the scaled 8x8 electric combat vehicle are a solid foundation for the development of future full-size 8x8 electric combat vehicles.
PSD Profiles for Dynamic and Durability Tests of Military Off-Road Vehicle Racks
Authors: Velardocchia Mauro , Bonisoli Elvio , Tota Antonio , Lisitano Domenico , Paciullo Genny , Trevisi Marco
Published: April 2023

In a military off-road vehicle, generally designed to operate in an aggressive operating environment, the typical comfort requirements for trucks and passenger cars are revised for robustness, safety and security. An example is the cabin space optimisation to provide easy access to many types of equipment required on-board. In this field, racks hung to the cabin chassis are generally used to support several electronic systems, like radios. The dynamic loads on a rack can reach high values in the operative conditions of a military vehicle. Rack failures should be prevented for the safety of driver, crew and load and the successful execution of a mission. Therefore, dynamic and durability tests of these components, including the fixtures to the vehicle, are required. The capability to apply in a laboratory a dynamic load equivalent to the one experienced in a real mission opens the possibility to make durability tests in a controlled environment, to repeat them according to a defined methodology, potentially to accelerate the tests themselves, with clear benefits if the same validation should be done, otherwise, just on a proving ground. The definition of the excitation profiles for accelerated tests is not an easy task for the considered vehicle family. This paper proposes some guidelines to define realistic Power Spectral Density (PSD) profiles for dynamic and accelerated durability tests, based on the on-board actual vibrations measured levels. The PSD profiles are a combination of the vibration acquired on-board on several different stationary paths, synthesised on the vehicle life cycle environmental profile. The proposed approach aims at limiting expensive on-road tests for the dynamic and durability assessments of military vehicle equipment’s.
Exploration of Support Methods for Tradespace Exploration
Authors: Sutton Meredith , Wagner John , Turner Cameron , Hartman Gregory , Gorsich David , Skowronska Annette , Rapp Stephen
Published: April 2023

Tradespace exploration (TSE) is an important aspect of the early stages of the design process, in which stakeholders search for the most optimal solutions within a design variable-bounded solution space. This decision-making process requires stakeholders to understand the trade-offs and compromises that may be required to choose a solution. In order for stakeholders to make these decisions appropriately, information must be presented in an efficient manner and should ensure that the trade-offs between solutions are clearly visible. Existing visualizations often struggle to elucidate these trade-offs, and can rapidly become difficult to understand as the dimensionality of the tradespace increases. In this paper, the benefits and drawbacks to these existing methods will be discussed. In addition, this paper will explore potential methods to improve information presentation for TSE, including framing, visual steering, and visualization options. A three-phase study plan is then proposed to determine the effects of implementing these suggested improvements. The three phases of this study include various degrees of technological intervention with regard to how the tradespace is represented, including morphological charts, radar plots, and virtual reality-supported hyper-dimensional plots.
Modeling and Analysis of Fully Electric and Hydrogen-Powered Bradley Fighting Vehicles
Authors: Mittal Vikram , Figueroa-Santos Miriam
Published: April 2023

As the U.S. Army moves to electrify portions of its vehicle fleet, it is worth considering the heavier combat vehicles. However, the high power demand of these vehicles coupled with the relatively low energy density of modern batteries result in electric vehicles with limited range and functionality. Hydrogen-based fuel cells are an alternative to batteries that can provide many of the same environmental and logistical benefits associated with electrification. This study models the energy consumption for two variants of the M2A4 Bradley Fighting Vehicle (BFV). The first variant is powered by a hydrogen-based Proton Exchange Membrane Fuel Cell; the second variant is powered through lithium-ion batteries. These models account for vehicle weight, accelerative forces, drag, road grade, tractive losses, and ancillary equipment and are compared against a conventional M2A4 BFV. The analysis also considers the weight and volume restrictions for the powertrain especially as they relate to the storage of hydrogen and batteries. In doing so, the range of the vehicle with each powertrain can be determined. Furthermore, the study looks at the logistical needs associated with such vehicles. In particular, it approximates the quantity of fuel, water, and solar panels required to produce enough electricity to recharge batteries or electrolyze water for hydrogen production. The analysis then evaluates the trade-offs between vehicle range and logistical footprint associated with the different powertrains. The study then concludes with a discussion on the technical challenges associated with each powertrain.
Physical-Neural Network Hybrid Modeling Method for Dynamic Characteristics of Air Springs with Auxiliary Chambers
Authors: Zheng Yiqian , Shangguan Wenbin
Published: April 2023

Air springs with auxiliary chambers (ASAC) are widely used in automotive suspension systems. The introducing of the auxiliary chamber and the connecting flow passage makes the system more complex, especially in which case an additional resonance peak caused by the air inertia in a connecting pipe appears. To characterize the nonlinear dynamic characteristics, this paper proposes a novel physical-neural network hybrid modeling method for ASACs. Firstly, experiments are carried out to measure the dynamic characteristics of ASACs. Then, based on the thermodynamic principle, a nonlinear dynamic characteristic model for the ASAC is developed and a linearized process is performed to obtain a linearized physical model. Due to the amplitude dependence and frequency dependence in the dynamic characteristics of ASACs, the physical model cannot accurately characterize these nonlinearities. To compensate for the errors caused by the uncaptured frictional damping and nonlinear air resistance, a neural network model is developed. The proposed hybrid models are validated to be more accurate than a physical model. The proposed modeling method provides a guideline for the modeling of other nonlinear components in vehicles.
The Multi-Objective Optimization Design of Hard Point Parameters for Double Wishbone Independent Suspension
Authors: Zhang Suo , Gao YK , Gao De , Pan Ting
Published: April 2023

There are often a large number of design variables and responses in suspension hard point optimization design. The traditional optimization strategy integrating heuristic algorithm and simulation model is not applicable due to its low efficiency. To solve optimization problems with huge number of design variables and responses, a multi-objective optimization framework combined heuristic optimization algorithm with multi-objective decision-making method is developed. Specifically, the multi-objective optimization was performed by dividing the problem into two independent sub-problems of multi-objective optimization and multi-objective decision-making. Further, to reduce the number of sample points required for building a surrogate model, a two-stage multi-objective optimization is proposed. In the first stage, the initial optimal solution is obtained based on the experimental design (DOE), and the influence of each design variable on each response is obtained through sensitivity analysis; the second stage trains the mixed surrogate model around the initial optimal solution, and then performs multi-objective particle swarm optimization design based on the mixed surrogate model, and finally obtains a satisfactory Pare Frontier. Furthermore, to overcome the limitations brought by a single multi-objective decision-making method, a multi-objective decision-making method developed by combining a weight strategy inspired by grey relational analysis and entropy analysis was applied to determine multiple objectives weights from the Pareto frontier. Finally, the pseudo-damage of each connection point of the suspension based on the hard point parameters optimized by the proposed optimization strategy is better than the original suspension, i.e., the pseudo-damage of each connection point is improved by 21.35%, 35.96%, 12.04%, 14.65%, 25.28%, 14.31%, 16.35%, 20.76%, 12.09%, 11.41%, 14.63%, 11.02%, 33.92%, 33.98%, 47.48%, 85.09%, respectively.
New Low-GWP Refrigerants for Electric Vehicle Heat Pump with Superior Comprehensive Performance
Authors: Yu Binbin , Qian Chenyi , Ouyang Hongsheng , Shi Jun-Ye , Guo Zhikai , Chen Jiangping
Published: April 2023

The heat pump with low global warming potential (GWP) refrigerants is imperative for the electric vehicle (EV) to slow down global warming and extend the driving range while meeting passengers' thermal comfort in low ambient temperatures. However, there are no appropriate refrigerants. To provide long-term and environmental-friendly refrigerants in the heat pump for EVs, herein, we reported newly developed low-GWP refrigerant mixtures, i.e., DL3B, whose GWP is lower than 140, the flammability (lower flammability limit and burning velocity), saturation pressure, lubricant miscibility, material compatibility were experimentally tested. A test bench that can investigate the performance of an R410A prototype was built. The drop-in tests of the DL refrigerant were carried out to evaluate the capacities and COPs for both cooling and heating modes in the EV heat pump system. Results showed that DL3B has similar saturation pressure to R410A, good miscibility with original lubricant and is compatible with both metallic and non-metallic materials. 6.The heating capacities of DL3B were 101.8-112.8% of the R410A system, with COP being 84-99.8%, while the cooling capacities showed 118.9-128.4% of the R410A system, with COP being 98.2-108%. DL3B showed very weak flammability and can be classified as A2L according to the ASHRAE standard. Besides, our real car road test showed very good heating performance even in -25 °C ambient temperature with similar warm-up performance to R410A. Our results certificated the promising potential application of the DL refrigerant in EV heat pumps.