bluuebunny/crossref_metadata_2025 huggingface dataset:
Development and Validation of Dynamic Programming based Eco Approach and Departure Algorithm
Authors: Goyal Vasu , Dudekula Ahammad Basha , Naber Jeffrey
Published: April 2024

Eco Approach and Departure (Eco-AnD) is a Connected Automated Vehicle (CAV) technology aiming to reduce energy consumption for crossing a signalized intersection or set of intersections in a corridor that features vehicle-to-infrastructure (V2I) communication capability. This research focuses on developing a Dynamic Programming (DP) based algorithm for a PHEV operating in Charge Depleting mode. The algorithm used the Reduced Order Energy Model (ROM) to capture the vehicle powertrain characteristics and road grade to capture the road dynamics. The simulation results are presented for a real-world intersection and 20-25% energy benefits are shown by comparing against a simulated human driver speed profile. The vehicle-level validation of the developed algorithm is carried out by performing closed-course track testing of the optimized speed solutions on a real CAV vehicle. A controlled intersection system with simulated signal phase and timing (SPaT) was used to establish the desired inputs for DP. Further, analysis is made to understand the computational efforts needed for the developed DP algorithm for different discrete levels and its effects on algorithm performance.
Comparison of Neural Network Topologies for Sensor Virtualisation in BEV Thermal Management
Authors: Wray Alex , Pipes Harry , Dutta Nilabza , Ebrahimi Kambiz
Published: April 2024

Energy management of battery electric vehicle (BEV) is a very important and complex multi-system optimisation problem. The thermal energy management of a BEV plays a crucial role in consistent efficiency and performance of vehicle in all weather conditions. But in order to manage the thermal management, it requires a significant number of temperature sensors throughout the car including high voltage batteries, thus increasing the cost, complexity and weight of the car. Virtual sensors can replace physical sensors with a data-driven, physical relation-driven or machine learning-based prediction approach. This paper presents a framework for the development of a neural network virtual sensor using a thermal system hardware-in-the-loop test rig as the target system. The various neural network topologies, including RNN, LSTM, GRU, and CNN, are evaluated to determine the most effective approach. The solution proposed intends to use a combination of the states determined in other sensors and the control inputs made into the system to predict the state of the sensor to be virtualised, with the aim of an average accuracy of 95% and a worst-case accuracy of 80%. Also discussed are the potential methods of nonlinear system identification that can be used to achieve these goals, concluding through a literature review that a Neural Network solution is the most probable method to produce an accurate result. Based on this an analysis is performed of the challenges of neural network development, from collecting and processing data, to actually training the neural network and evaluating the performance outcome. Establishing that depending on the quality and quantity of data collection a range of methods that could be implemented.
Application of Machine Learning to Engine Air System Failure Prediction
Authors: Li Yong , Hui Hongjun , Shuai Shijin , Qin Yu , Shao Peng , Liu Zemin
Published: April 2024

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state). The precisions of our model are 89.1% and 92.9% on training dataset and field test dataset, respectively. The average time gap between prediction and failure is 45 days, which means the model can help our end users and service engineers take actions to avoid sever failure 45 days in advance. There are also two applied cases of the model to real vehicles. In both cases, the model successfully detects the sub-health state and helps service engineers repair the air system in advance. After the repair, the state indicator was recovered to the normal level, which can be a validation of our model. The algorithm could be generalized to failure of other vehicle parts with similar conditions and save money and time for our customers.
Design Method for Integrating Trained Neural Nets with UML
Authors: Arai Masatoshi
Published: April 2024

Model-based developments have been introduced to reduce the development time for vehicle systems. Various model-based tools, including MATLAB and Simulink, have been introduced, and each vehicle component uses different tools to model assets. This makes the system complex and reduces the simulation efficiency because of the need for interfaces or converters when reusing model assets and combining parts. However, machine learning, in which neural nets are pretrained to make inferences in real time, is being applied to automatic driving and applications such as object recognition. This study developed a system in which the inputs and outputs assigned to a model were trained using neural nets, and the trained neural nets were combined with UML: Unified Modeling Language. A previous UML integration proposal integrated C/C++ code automatically generated from the models. Therefore, the previous proposal made limited use of modeling tools with automatic code generation capabilities. The learned network can be easily imported by adding input/output capabilities to the standard UML. While UML enables humans to understand the entire development system and prevent design errors, it becomes more complex when details are expressed. In general, UML has been used for overall design and has never been integrated with a detailed design. However, in this system, a detailed design is created by the designer using an arbitrary modeling tool and is integrated electronically, thereby reducing design errors. Furthermore, the use of pretrained neural nets reduces the simulation time and improves the development efficiency. There is also a proposal to easily switch between models created using UML and deep learning neural networks.
Assessing Powertrain Technology Performance and Cost Signposts for Electrified Heavy Duty Commercial Freight Vehicles
Authors: Sujan Vivek , Galigekere Veda Prakash
Published: April 2024

Adoption of fuel cell electric vehicles (FCEV) or battery electric vehicles (BEV) in heavy-duty (HD) commercial freight transportation is hampered by difficult technoeconomic obstacles. To enable widespread deployment of electrified powertrains, fleet and operational logistics need high uptime and parity with diesel system productivity/total cost of ownership (TCO), while meeting safety compliance. Due to a mix of comparatively high powerplant and energy storage costs, high energy costs (more so for FCEV), greater weight (more so for BEV), slow refueling / recharging durations, and limited supporting infrastructure, FCEV and BEV powertrains have not seen significant uptake in the HD freight transport market. The use of dynamic wireless power transfer (DWPT) systems, consisting of inductive electrical coils on the vehicle and power source transmitting coils embedded in the roadways, may address several of these challenges. An appropriately designed BEV, will absorb energy at highway speeds from these transmitting coils in the road, providing electrical energy to sustain its mission. This has the potential to reduce the onboard energy storage requirements for BEV while enabling significantly longer missions. While still contingent on considerable infrastructure development, this technology has the potential to disrupt the zero emission HD freight transport system by not only lowering the overall total cost of ownership and increasing asset uptime, but also reducing the use of rare earth minerals required to support the deployment of these vehicle systems. This paper presents a study of four use cases (Drayage, Short Haul, Regional Haul, and Long Haul) of HD vehicles comparing the diesel incumbent powertrain against FCEV, BEV with depot charging, and BEV with DWPT charging. By considering the interplay of several technoeconomic factors associated with each of these powertrain options and further considering real world vehicle weight and road variations, a systematic study is conducted to show critical signposts for both single and multi-parameter technology viability. This study also assesses the sensitivity of each factor to the overall TCO changes thus identifying critical areas of further research and development. Finally, by considering the four use cases together a preliminary strategy to introduce DWPT in freight roadway networks is stipulated. Future works will address the specific characteristics and develop this strategy more holistically based on freight volume, road conditions, and other key development factors.
A Manufacturing Performance Comparison of RSW and RFSSW Using a Digital Twin
Authors: Gale Damon , Hovanski Yuri , Coyne Jeremy , Namola Kate
Published: April 2024

The design of lightweight vehicle structures has become a common method for automotive manufacturers to increase fuel efficiency and decrease carbon emission of their products. By using aluminum instead of steel, manufacturers can reduce the weight of a vehicle while still maintaining the required strength and stiffness. Currently, Resistance Spot Welding (RSW) is used extensively to join steel body panels but presents challenges when applied to aluminum. When compared to steel, RSW of aluminum requires frequent electrode cleaning, higher energy usage, and more controlled welding parameters, which has driven up the cost of manufacturing. Due to the increased cost associated with RSW of aluminum, Refill Friction Stir Spot Welding (RFSSW) is being considered as an alternative to RSW for joining aluminum body panels. RFSSW consumes less energy, requires less maintenance, and produces more consistent welding in aluminum as compared to RSW. Research has shown that RFSSW is capable of producing joints of similar strengths at comparable cycle times to that of RSW. This paper presents a manufacturing performance comparison of RSW and RFSSW. Using FlexSim DES, a digital twin model of a real production welding cell using RSW on aluminum was created. The same welding cell was then modelled using RFSSW. For this study, a door assembly produced by Toyota North America was selected. The fully automated weld cell consists of 9 industrial robots making 8 unique joints, totaling 85 welds per door. Using the DES model, metrics like cycle times, throughput, etc. were evaluated on a shift level and compared between the processes. In summary, this study provides valuable insights into the comparative manufacturing performance of RSW and RFSSW, shedding light on their respective strengths and weaknesses in a production setting.
Formula 1 Race Car Aerodynamics: Understanding Floor Flow Structures and Why It Is a Key Component in Modern Racing
Authors: Shaalan Amr , Assanis Dimitris , Raman Aditya , Wijeyakulasuriya Sameera , Senecal Kelly
Published: April 2024

This paper delves into the intricate realm of Formula 1 race car aerodynamics, focusing on the pivotal role played by floor flow structures in contemporary racing. The aerodynamic design of the floor of a Formula 1 car is a fundamental component that connects the flow structures from the front wing to the rear end of the car through the diffuser, thus significantly influencing the generation of lift and drag. In this work, CFD was used to predict the structure of the vortices and flow pattern underneath a Formula 1 car using a CAD model that mimicked the modern Red Bull Racing Team’s car in recent years. Through comprehensive analysis and simulation, a detailed understanding of the complex flow patterns and aerodynamic phenomena occurring beneath the floor of the car and its vicinity is presented. This entails a close examination of how air interacts with the floor of the car and how the flow around the car can be manipulated to alter the flow rate and the quality of air going into the diffuser, generating crucial insights into the underlying principles at play. Finally, special attention was focused on the tire squish area and the resulting structures affecting the diffuser. Vortex structures were illustrated utilizing volume renders of vorticity and velocity in the domain, alongside Velocity-based Line Integral Convolution (LIC) total pressure contours at the diffuser. The assessment was carried out for three different speeds of 30 m/s, 50 m/s, and 90 m/s with two different ride heights for each speed. This research aims to shed light and understand the critical factors that engineers and designers consider when optimizing Formula 1 race car aerodynamics, how different geometric elements interact, and why it is considered a difference maker in modern racing.
Lightweight Design of Integrated Hub and Spoke for Formula Student Racing Car
Authors: Cui Jiarui , Chen Yichao
Published: April 2024

In the racing world, speed is everything, and the Formula Student cars are no different. As one of the key means to improve the speed of the car, lightweight plays an important role in the racing world. The weight reduction of unsprung metal parts can not only improve the driving speed, but also effectively optimize the dynamic of the car, so the lightweight design of unsprung parts has attracted much attention. In the traditional Formula Student racing car, the hub and spoke are two independent parts, they are fixed by four hub bolts or a central locking nut, the material of these fasteners is usually steel, so it brings a lot of weight burden. In order to achieve unsprung lightweight, a new type of wheel part design of Formula Student racing car is proposed in this paper. The hub and spoke are designed as integrated aluminum alloy parts, effectively eliminating the mass of hub bolts or central locking nuts. After proper iterative optimization, the part achieves a weight reduction of more than 25% compared to the traditional solution. The part uses CATIA software for structural modeling design, and uses ANSYS software for finite element analysis. In order to further verify the design effect, the design was applied to the 2023 race car of the WUTE team of Wuhan University of Technology and participated in the Formula Student Electric China (FSEC). Through simulation and real car running tests, it is proved that the part is safe and reliable, and prove that the parts can be lightweight at the same time meet the requirements of the car running condition.
Numerical Study on the Design of a Passive Pre-Chamber for a Heavy-Duty Hydrogen Combustion Engine
Authors: Maas Ralph , Bekdemir Cemil , Somers Bart
Published: April 2024

Lean-burn hydrogen internal combustion engines are a good option for future transportation solutions since they do not emit carbon-dioxide and unburned hydro-carbons, and the emissions of nitric-oxides (NOx) can be kept low. However, under lean-burn conditions the combustion duration increases, and the combustion stability decreases, leading to a reduced thermal efficiency. Turbulent jet ignition (TJI) can be used to extend the lean-burn limit, while decreasing the combustion duration and improving combustion stability. The objective of this paper is to investigate the feasibility of a passive pre-chamber TJI system on a heavy-duty hydrogen engine under lean-burn conditions using CFD modelling. The studied concept is mono-fuel, port-fuel injected, and spark ignited in the pre-chamber. The overall design of the pre-chamber is discussed and the effect of design parameters on the engine performance are studied. From this analysis, it was found that the volume of the pre-chamber and the area of the pre-chamber holes have major impact on the performance of the pre-chamber. Next, the difference between a regular spark-ignited combustion and a TJI system are investigated at a medium load point. The combustion duration is shortened significantly using a passive pre-chamber. However, the heat transfer loss through the walls increased significantly due to prolonged higher temperatures and higher turbulence near the combustion chamber walls. Finally, the air-fuel ratio is increased to study its effect on the heat transfer loss and NOx emissions.
Leveraging DOConFilter to Improve Exhaust System Packaging
Authors: Kinoshita Takashi , Tanaka Katsunori , Furuta Yasuyuki , Aoki Takashi , Sakamoto Hirofumi , Fakih Hussein , Fukumi Yuki , Yoshioka Fumihiko , Kato Kyohei
Published: April 2024

Diesel Particulate Filters (DPF) made of cordierite are generally used for diesel engine aftertreatment systems in both on-road and commercial off-highway vehicles to meet today’s worldwide emission regulations. PM/PN and NOx emission regulations will become more stringent worldwide, as represented by CARB2027 and Euro7. Technologies that can meet these strict regulations are required. As a result, aftertreatment systems have become more complex with limited space.

Recently, off-highway OEMs have been interested in downsizing the aftertreatment system using concepts such as DOConFilter in an effort to reduce the size of the exhaust system. DOConFilter can effectively replace DOC + CSF or DOC + bare DPF systems with a single zone coated particulate filter.

DOConFilter systems have an increased amount of coating compared to CSF as higher-filtration filters will become the norm. An undesirable increase in pressure drop is expected by adopting this new technology. In addition, soot regeneration efficiency will be another challenge in the application of this new technology. Therefore, optimization of the DOConFilter material and filter cell structure is needed in order to achieve aftertreatment system downsizing, while minimizing any system drawbacks.

NGK has developed several Cd-DPF materials which will be optimal for future regulations. NGK has also focused on the integration of high cell density and thin wall cell structures for effective soot regeneration efficiency.

In this paper, performance of both large and conventional cell structures has been compared under the DOConFilter catalyst. The DOConFilter catalyst included both conventional and newer materials for future tighter regulations. Pressure drop performance with and without soot have been evaluated before and after coating.

In addition, soot regeneration efficiency performance has also been evaluated to assess concerns on DOConFilter. With these results, we will show how this innovation will bring benefits to future aftertreatment systems.
Research on Intelligent Shift Strategy for Heavy Vehicles Based on Predictive Information
Authors: Zhang Junfeng , Chen Daxin , Wang Gaoxiang
Published: April 2024

By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after detaching from the experience of good drivers, the current shifting strategy is limited to the vehicle state at the current moment, and cannot make predictive judgment of the road environment ahead, and problems such as cyclic shifting will occur due to insufficient power when driving on the ramp. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy. The vehicle power demand is calculated based on the possible future working conditions and road information, and the rotation speed, torque and impact degree are constrained to ensure the rationality of the shift range under the premise of meeting the vehicle dynamic performance. Finally, the optimal gear sequence planning is carried out with the cumulative fuel consumption in the next 5 seconds as the economic objective and output at the corresponding time. Based on GT-Suite simulation platform, the vehicle object model and gearshift control strategy are established. Under different driving conditions and road scenes, the gearshift strategy of the real vehicle is compared with the gearshift strategy built in this paper. The simulation results show that compared with the real vehicle gearshift strategy, the predictive intelligent gearshift strategy improves the fuel consumption by about 0.2% ~ 0.78%, and has better adaptability in the dynamic driving environment; Compared with the comprehensive performance shift strategy, this strategy reduces the frequent gear shift caused by the gradient change of the comprehensive shift strategy, and the fuel consumption is reduced by about 1.22% under the actual road test condition.
Optimum Shifting of Hybrid and Battery Electric Powertrain Systems with Motors before and after a Transmission
Authors: Tuller Zachary , Patel Nadirsh , Walsh McKenzie
Published: April 2024

This paper proposes an optimization-based transmission gear shifting strategy for electrified powertrains with a transmission. With the demand for reduced vehicle emissions, electrified propulsion systems have garnered significant attention due to their potential to improve vehicle efficiency and performance. An electrified propulsion system architecture of significance includes multiple electric motors and a transmission where some driveline actuators can transmit torque through changing gear ratios. If there is at least one electric motor arranged before the input of the transmission and at least one after the transmission output, a unique design opportunity arises to shift gears in the most energy efficient manner. An optimization-based gear shifting strategy is proposed where torque through the transmission is offloaded to the electric motor arranged after the transmission’s output, the transmission shifts gears with less torque transmitted through it, then the base optimization strategy is resumed after the gear shift. This optimization strategy improves energy efficiency by reducing clutch losses during the torque and speed phases of the gear shift.

The optimization solution for shifting gears in electrified powertrain systems with transmissions is described starting with an analysis of electrified powertrains that can implement this strategy. The optimization-based strategy is described in detail, showing the propulsion system maximizes energy efficiency considering a variety of operating conditions and gear shifting methods. Propulsion system efficiency is presented with an emphasis on electric motor power losses and clutch losses. Finally, a variance analysis is presented showing the impact of system parameters such as gear ratio spread on optimization.
CFD Methodology for Torque Converter Clutch Slipping Modeling
Authors: Jeyabalan Subramanian
Published: April 2024

In torque converters, a lockup clutch is used for direct torque transfer from the engine to the gearbox. Nowadays, earlier lockup engagement is necessary to reduce fuel consumption. It introduces noise and vibration issues in the transmission that are solved by clutch slipping. However, the clutch experiences much heat because of earlier engagement, which needs to be adequately dissipated by ATF oil. To overcome this issue, multi-plate clutches are commonly used for efficient torque transfer and clutch slipping. On the other side, packaging space for torque converters is reducing at the vehicle level, especially in hybrid vehicles, which reduces the efficient cooling of clutches. So, accurate modeling of clutch slipping is necessary to improve the clutch performance and durability of the product. Clutch slipping is a transient phenomenon that involves conjugate heat transfer and rotational flow modeling. There are different ways to model clutch slipping in CFD simulations. One of the modeling methods is applying the power loss as heat flux in clutch facings. However, heat flux is a vector quantity, and its direction is defined. That means the model introduces the approximation in heat transfer direction and reduces calculation accuracy.

In this paper, power loss is applied as an energy source, which is a scalar quantity, and modeling methodology is explained. With this methodology, CFD calculation results are correlated well with test measurement, allowing to match the clutch design with the challenging packaging constraints.
Impact of Automated Driving on Design and Energy Consumption of Electrified Drives
Authors: Sturm Axel Wolfgang , Henze Roman , Küçükay Ferit
Published: April 2024

This paper discusses the dependency between powertrain design and automated driving. The research questions are to what extent automated driving influences the powertrain design and how energy and fuel consumption is affected in comparison to customer driving. For this investigation a concept study is carried out for a D-segment vehicle and multiple powertrain topologies, ranging from non-electrified to plug-in hybrids and battery electric vehicles. In order to answer the research questions, the used development process and the methods for optimizing the drive system are presented accordingly, taking into account all vehicle requirements, the drive system and the components and their interactions with each other. This work focuses on two automated driving functions developed at the Institute of Automotive Engineering of the Technische Universität Braunschweig. The functions are an “automated valet parking” and a “highway pilot”. The hardware architecture required for automated driving functions lead to an increase in vehicle mass and auxiliary power consumption. Furthermore, the automated driving functions result in changed driving profiles. Driving cycles were generated on the basis of measurement data from the automated functions and compared with the customer's driving operation. The results show, that an energy reserve for an automated valet parking function leads to a reduction in the all-electric range up to 12 km for battery electric vehicles and 7 km for plug-in-hybrids and thus also to up to 2 g/km higher combined emissions. It has also been shown that the impact of the highway pilot to energy and fuel consumption in customer operation is significantly influenced by the customer's driving style and the additional consumption for the automated driving function, with battery electric vehicles having the highest savings potential.
Development of an Electric Medium Duty Commercial Demonstration Vehicle
Authors: Guo Chengyun , Van Maanen Keith , Liu Xiaobing , Chen Wei , Theunissen Frans , Rama Neeraj , Hegde Prashant
Published: April 2024

To better understand the technical challenges of commercial vehicle electrification, BorgWarner converted a production Internal Combustion Engine (ICE) medium duty truck into a fully electrified vehicle. The resulting vehicle includes a newly developed dual-motor rear Beam eAxle driven by a pair of high-performance silicon carbide (SiC) inverters, an 800V battery system, and a new thermal management system customized for the electric vehicle. This paper will detail the conversion process along with the key components involved in the build. The resulting performance of the fully electrified commercial vehicle will be presented in comparison to the original production vehicle. The primary aim is to outline what is entailed in an electric vehicle conversion and to share the learnings gained throughout this build and development process.
Design and Sizing Methodology of Electric Vehicle Powertrain to Achieve Optimal Range and Performance
Authors: Fardoun Abbas , Singh Sanjay
Published: April 2024

Battery electric vehicles are quickly gaining momentum to improve vehicle fuel efficiency and emission reduction. However, they must be designed to provide adequate range on a single charge combined with good acceleration performance, top speed, gradeability, and fast charging times. The paper presents a model for sizing the power train of an electric vehicle, including the power electronic converter, electric motor, and battery pack. A major assumption is that an optimal wheel slip rate can be achieved by modern vehicles using slip control systems. MATLAB/Simulink was used to model the vehicle powertrain. Simulations were conducted based on different speed and acceleration profiles. The purpose of the study focused on the motor and power electronics sizing requirements to achieve optimal range and performance.
Performance Parity Study of Electrified Class 8 Semi Trucks with Diesel Counterparts
Authors: Song Xubin , Ma Tiancai , Ebrahimi Kambiz , Jansons Marcis
Published: April 2024

It is recognized that the heavier vehicles, the more emissions, thus the more imperative to electrify. In this study, long haul heavy-duty trucks are referred as HDTs, which are recognized as one of the hard-to-electrify vehicle segments, though the automotive industry has gained trending advantages of electrifying both light-duty cars and SUVs. Since big rigs such as Class 8 HDTs have significant road-block challenges for electrification due to the demanding long-hour work cycles in all weathers, this study focuses on quantifying those electrification challenges by taking advantage of the public data of Class 8 tractors & trailers. Tesla Semi is the research target though its vehicle spec data is sorted out with fragmentary information in the public domain. The key task is to analyze the battery capacity requirements due to environmental temperature and inherent aging over the lifespan. The investigation will go to compare the EV Semi performance with diesel counterparts, especially focusing on the operational cost.
Fuel Cell Powertrain Power Management with Super Capacitor
Authors: Sharma Prashant , Penta Amar , Garg Mudit , Dey Supriyo , Agrawal Mridul
Published: April 2024

Nowadays, increasing greenhouse gas emissions and economic considerations leads to the seek for cleaner and sustainable solutions. The exponential rise of number of on road vehicles in recent past lead to environmental problems to alarming situation due to increasing greenhouse gases. In 2020, global Co2 emissions was 33908 Mt Co2 & out of which 7153 Mt Co2 from transportation sector. Hydrogen fuel based internal combustion engine & fuel cell can lead the way for the global goal to achieve zero greenhouse gas emission. Though hydrogen fuel cell usage in the mobility application has its own limitation due to its slow dynamic response to the driver demanded power. In order to sync with transient and dynamic demand behavior of vehicles, Powertrain needs to deliver instant drive torque to the wheels, which is difficult to achieve from fuel cell powertrain (fuel cell + HV Battery Pack) alone. Our research emphasis on research of Fuel cell & Super capacitor hybrid power source to deliver transient and dynamic power supply to electric powertrain. The super capacitor is arranged in parallel to the fuel cell to overcome the limitation of fuel cell. The study proposes different use case scenarios and optimized power management strategies to meet the dynamic vehicle requirements. The use case scenarios are such that they replicate the actual vehicle condition where the optimization is required for the power management. Vehicle charge power mode and discharge power mode is considered for our research. The three major test case scenarios are explored, like vehicle start, Acceleration & regeneration for this paper.
Rapid assessment of power battery states for electric vehicles oriented to after-sales maintenance
Authors: Yuan Yongjun , Shao Yuxin , Jiang Bo , Wang Xueyuan , Dai Haifeng
Published: April 2024

With the continuous popularization of electric vehicles (EVs), ensuring the best performance of EVs has become a significant concern, and lithium-ion power batteries are considered as the essential storage and conversion equipment for EVs. Therefore, it is of great significance to quickly evaluate the state of power batteries. This paper investigates a fast state estimation method of power batteries oriented to after-sales and maintenance. Based on the battery equivalent circuit model and heuristics optimization algorithm, the battery model parameters, including the internal ohmic and polarization resistance, can be identified using only 30 minutes of charging or discharging process data without full charge or discharge. At the same time, the proposed method can directly estimate the state of charge (SOC) and maximum available capacity of the battery without knowing initial SOC information. In order to further improve the efficiency and accuracy of this method, the performance of various optimization algorithms is compared. Finally, we utilized two kinds of lithium-ion power battery, including 117Ah and 156Ah capacity levels, to verify the proposed method. The experimental results indicate that the estimation error of capacity and SOC was controlled within 2.3%, and the estimation error of internal resistance was within 10%. The proposed state estimation method provides a solution for quickly assessing EVs batteries' state of life and remaining utilization value.
Optimal PWM Schemes in Wound Rotor Synchronous Machines and IPM Synchronous Machines for Maximum System Efficiency: A Comparative Study
Authors: Ma Cong , Tyckowski Joseph
Published: April 2024

Wound rotor synchronous machines (WRSM) without rare-earth magnets are becoming more popular for traction applications, but their potential in drive performance has not yet been fully explored. This paper presents a Pulse Width Modulation (PWM) scheme optimization procedure to minimize motor and inverter losses. It leverages different PWM schemes with different PWM switching strategies and switching frequencies. First, a generic PWM-induced motor loss calculation tool developed by BorgWarner is introduced. This tool iteratively calculates motor losses with PWM inputs across the entire operating map, significantly improving motor loss prediction accuracy. The inverter losses are then calculated analytically using motor and wide-bandgap (WBG) switching device characteristics. By quantifying these various scenarios, the optimal PWM scheme for achieving the best system efficiency across the entire operating map is obtained. The PWM-induced motor loss characteristics, the system loss tradeoffs, and the resulting optimal efficiency are discussed in detail. Finally, a comparison between IPMSMs and WRSMs in terms of system efficiency is presented. Discussions on the differences of PWM-induced losses and optimal modulation schemes between WRSMs and IPMSMs are provided to understand the tradeoffs in selecting different motor topologies.
Optimization of Laminated Stack Solutions for Electric Motors in Electrified Vehicles
Authors: Van Der Sluis Francis , Seitzinger Benny , De Vet Sander , Alexandrov Oleg , Kruijswijk Emile , Herzberger Andreas
Published: April 2024

The electrification of vehicles marks the introduction of new products to the automotive market and a continued effort to optimize their performance. The electric motor is an important component with which a further optimization of efficiency, power density and cost can be achieved. Additional benefits can be realized in the laminated core. This paper presents an innovative method to produce laminated stacks by a chain of processes different from conventional ways. The process chain presents a sequence of precision blanking, buffering, heat treatment and gluing. The effect of these processes is compared with existing solutions that typically contain some individual features but usually not the combination that enhances the overall effect.

The heat treatment decreases residual stresses from previous process steps and reduces power losses in the laminated core. Depending on the design, benefits around 20% are found. The bonding of lamellae by gluing maintains their flatness and prevents short circuits between lamellae by other processes like interlocking or welding. This reduces the occurrence and impact of eddy currents and the associated power losses. Lower power losses increase power density of the stack and electric motor. The presented manufacturing process also supports this by an improved stacking factor. The improved efficiency reduces thermal stress on critical electric drive components and leads to higher (continuous) power at the system level. Alternatively it can help to reduce the volume and weight of the motor, auxiliary systems and battery, leading to a more cost effective solution.
Advanced Development of e-HMI Road Content Projection Headlamp
Authors: Kim Hyeong Seon
Published: April 2024

Recently, with the advancement of autonomous driving technology, the function of external lamps has been changed. Previously, the focus was on the visibility of drivers, but with the advancement of autonomous driving technology, the concept of autonomous driving systems has been developed. Accordingly, the trend of automotive lamp lighting systems has been developed in terms of design, e-HMI (exterior-human machine interface), It is developing in accordance with three major fields such as sensor connection. Therefore, this paper will cover the prior development of road content projection headlamps that enable e-HMI implementation to reflect these new trends. Since the technology is mass-produced and sold by several manufacturers, our company also needs to quickly develop and apply the technology in advance. Only four types of symbols are allowed in European law. Although it is still impossible for the symbols to be guided in the direction of progress, it is expected that they will be allowed soon as the European law discussion is actively reviewing the permission. This paper includes a detailed review for setting the symbol position of the road projection, a process for setting the light source module, reviewing development goals such as contrast ratio/equality/sharpness, and a process for reviewing formulas to establish detailed size requirements for symbols projected on the road surface. Based on this research process, we will discuss two concepts of road projection light source structure that were finally developed, and detailed projection quality of road symbols that satisfy the development goal. We will also introduce various reviewed road symbols and video scenarios.
Multi-Objective Optimization of Occupant Survival Space of a Medium-Duty Vehicle under Rollover Condition
Authors: Zhang Jiangfan , Zou Xiaojun , Yuan Liu-kai , Zhang Tang-yun , Wang Tao , Wang Liangmo
Published: April 2024

Due to the high center of gravity of medium-duty vehicles, rollover accidents can easily occur during high-speed cornering and lane changes. In order to prevent the deformation of the body structure, which would restrict the survival space and cause compression injuries to occupants, it is necessary to investigate methods for mitigating these incidents. This paper establishes a numerical model of right-side rollover for a commercial medium-duty vehicle in accordance with ECE R66 regulations, and the accuracy of the model is verified by experiment. According to the results, the material and size parameters of the key components of the right side pillar are selected as design variables. The response result matrix was constructed using the orthogonal design method for total mass, energy absorption, maximum collision acceleration, and minimum distance from the survival space. A multi-objective optimization of 25 sets of sample points was performed using a multi-factor weight analysis method, with the highest weighted objective being the minimum distance between the pillar and the survival space. The results indicate an 11.3% increase in the minimum distance between the column and the survival space after a rollover, an 18.5% decrease in peak acceleration, and a 13.7% reduction in total body weight. This improves the rollover safety of the entire vehicle.
The Influence of Sample Geometry on the Mechanical Properties and Failure Mechanisms of 6111 Aluminum Alloy Tensile Specimens
Authors: Gao Zhongfang , Chen Xiaoming , Zheng Xiaowan , Yang Lianxiang
Published: April 2024

This research focuses on the commercial 6111 aluminum alloy as the subject of investigation. By designing tensile specimens with the same characteristic dimensions but varying fillet radii, the effects of fillet radius on the tensile properties and stress concentration effects of the aluminum alloy were studied through tensile testing and digital image correlation techniques. The results demonstrate that with an increase in fillet radius, the failure strength and stress distribution of the aluminum alloy specimens have both undergone alterations. This phenomenon can be attributed to the reduction of stress concentration at the fillet due to the larger fillet radius. Further verification through digital image correlation reaffirms that samples with a fillet radius of 10mm exhibit notable stress concentration effects at the fillet, while specimens with a fillet radius increased to 40mm display uniform plastic deformation across the parallel section. The study also reveals that during the tensile process, dislocations migrate along slip planes inclined at a 45-degree angle to the stretching direction. The enlargement of fillet radius leads to a deceleration in dislocation movement rate and a decrease in dislocation density. As a result, material local strain hardening rate is reduced, and crack formation is suppressed. The established relationship between fillet radius and stress concentration location factor indicates that a smaller fillet radius corresponds to a weaker stress concentration location effect. This research sheds light on the significant influence of geometric shapes of aluminum alloy tensile specimens on their mechanical properties and deformation mechanisms. Moreover, it provides a theoretical basis for optimizing specimen design.
A Suspension Tuning Parameter Study for Brake Pulsation
Authors: Hong Hyung-Joo , Lee Changwook , Jun Hyochan , Zhu Dongzhe
Published: April 2024

Brake pulsation is a low frequency vibration phenomenon in brake judder. In this study, a simulation approach has been developed to understand the physics behind brake pulsation employing a full vehicle dynamics CAE model. The full vehicle dynamic model was further studied to understand the impact of suspension tuning variation to brake pulsation performance.

Brake torque variation (BTV) due to brake thickness variation from uneven rotor wear was represented mathematically in a sinusoidal form. The wheel assembly vibration from the brake torque variation is transmitted to driver interface points such as the seat track and the steering wheel. The steering wheel lateral acceleration at the 12 o’clock position, driver seat acceleration, and spindle fore-aft acceleration were reviewed to explore the physics of brake pulsation. It was found that the phase angle between the left and right brake torque generated a huge variation in brake pulsation performance.

Multiple analyses have been run to understand the relationship between the brake pulsation performance and suspension tuning. The suspension tuning parameters incorporated in the study were suspension bushing stiffness, bushing damping for a potential hydro-bushing implementation, the magnitude of the pulsation torque, unsprung mass, and spindle length.

Simulation results have demonstrated the physics behind the brake pulsation reasonably well. This study would enable engineers to find a good compromise of suspension tuning to improve brake pulsation in vehicle dynamics performance.
Numerical Simulation of Fluctuating Wind Noise of a Vehicle in Reproduced on-Road Wind Condition
Authors: Tajima Atsushi , Ikeda Jun , Nakasato Kosuke , Kamiwaki Takahiro , Wakamatsu Junichi , Oshima Munehiko , Li ChungGang , Tsubokura Makoto
Published: April 2024

In vehicle development, reducing noise is a major concern to ensure passenger comfort. As electric vehicles become more common and engine and vibration noises improve, the aerodynamic noise generated around the vehicle becomes relatively more noticeable. In particular, the fluctuating wind noise, which is affected by turbulence in the atmosphere, gusts of wind, and wake caused by the vehicle in front, can make passengers feel uncomfortable. However, the cause of the fluctuating wind noise has not been fully understood, and a solution has not yet been found. The reason for this is that fluctuating wind noise cannot be quantitatively evaluated using common noise evaluation methods such as FFT and STFT. In addition, previous studies have relied on road tests, which do not provide reproducible conditions due to changing atmospheric conditions. To address this issue, automobile manufacturers are developing devices to generate turbulence in wind tunnels. However, in wind tunnels, it is difficult to reproduce the large length-scale fluctuations of natural winds, and it could not sufficiently simulate the road conditions. In this study, we simulated the fluctuating wind that vehicles experience on the road and verified the fluctuating aerodynamic noise. We first reproduced wind noise under steady flow conditions and confirmed that the pressure fluctuation measured on the side window matched well with wind tunnel results up to 2 kHz. Furthermore, it was confirmed that using modulation power spectrum analysis, it is possible to quantitatively evaluate the fluctuating wind noise compared with FFT and STFT. From these results, we found that fluctuating wind noise is an acoustic phenomenon in which the aerodynamic noise generated around the vehicle is amplitude-modulated by fluctuations in the mainstream velocity. The technical challenge is to understand the separation flow around the A-pillar and side mirror, which generates fluctuating wind noise.