bluuebunny/crossref_metadata_2025 huggingface dataset:
Decarbonizing Light Vehicles with Hydrous Ethanol: Performance Analysis of a Range-Extended PHEV Using Experimental and Simulation Techniques
Authors: Dias Fábio Jairo , Lacava Pedro , Curto Pedro , Penaranda Alexander , Martinez Santiago , Weissinger Frederico , Martelli Andre , Santos Leila
Published: April 2024

Plug-in hybrid electric vehicles have the potential of combining the benefits of electric vehicle in terms of low emissions and internal combustion engine vehicles in terms of vehicle range. With the addition of a renewable fuel, the CO2 potential reduction increase even more. The last trends for PHEV are small combustion engine known as range extender, with battery package between full hybrid and electric powertrains. Thus, allowing an improvement in vehicle’s range, reducing battery materials while converting fuel energy through a highly efficient path. Although these vehicles have been proved to be a convenient strategy for decarbonizing the light vehicles, the use of alternative fuels is poorly studied. In this work, hydrous ethanol is chosen because is already available in some countries, such as USA and Brazil, and have an ultra-low well-to-tank CO2 emission. The study combines experimental and numerical tools for the development of an ultra-efficient and ultra-low emission powertrain in a range extender BMW i3 fueled with hydrous ethanol. Experimental tests were conducted in an engine test bench and a chassis dynamometer under FTP72 emission cycle. The vehicle simulation was performed in AVL Cruise M for the control strategy optimization and vehicle test under different driving conditions. For comparison, the vehicle was also tested with the battery electric version. In summary, this study demonstrates that the utilization of hydrous ethanol as a range-extender fuel in plug-in hybrid electric vehicles can significantly enhance vehicle range while reducing well-to-wheel CO2 emissions. The range-extender configuration, particularly with E100, exhibits promising potential, making it a competitive choice for drivers concerned about range limitations and environmental impact. The research emphasizes the adaptability of hydrous ethanol-fueled PHEVs across various driving scenarios, contributing to the ongoing global initiative to decarbonize light vehicles and combat climate change.
Optimization of BEV and FCEV Storage Design Based on Automated Packaging and Vehicle Simulation
Authors: Viehmann Andreas , Nauck Niklas , Esser Arved , Schramm Michael
Published: April 2024

Electrified vehicles represent mobility’s future, but they impose challenging and diverse requirements like range and performance. To meet these requirements, various components, such as battery cells, electric drives, fuel cells, and hydrogen vessels need to be integrated into a drive and storage system that optimizes the key performance indicators (KPI). However, finding the best combination of components is a multifaceted problem in the early phases of development. Therefore, advanced simulation tools and processes are essential for satisfying the customer´s expectation. EDAG Engineering GmbH has developed a flat storage platform, which is suitable for both, BEV and FCEV. The platform allows for the flexible and modular integration of batteries and hydrogen vessels. However, package space is limited and the impact of the design choices regarding the vehicle’s KPI need to be considered. Therefore, EDAG has developed a simulation model that combines automated 3D design and packaging for storage integration (battery cells and hydrogen vessels) with a simulation of the vehicle’s longitudinal dynamics. The model uses a cell database and automatically packages different cells into a predefined design space. For FCEV, it additionally packages hydrogen vessels in the remaining space. The model calculates the capacity and mass of each storage variant and uses them as input parameters for the vehicle longitudinal simulation. The main innovation of this contribution lies in the fact that it accounts for the 3D packaging of storage components enabling the analysis a multitude of design choices in the early concept phases and simulates their impact on the vehicle performance. Thus, decision-making processes in early development phases are supported and development time is significantly reduced. Within this contribution, two case studies for BEV and FCEV are performed investigating the influence of the package space provided for the energy storage on the vehicle performance and range highlighting the potential of the novel approach.
Traction Drives Electronic Torque Sensor
Authors: Smolin Viktor , Gladyshev Sergey , Goon Valentina
Published: April 2024

The paper solves the problem of increasing the accuracy of measuring torque and use of an electronic torque meter as a feedback sensor of synchronous and induction machines of an electric traction drive. Relevance of the problem and methods for its solving by indirect means using simulation models of electric machines are considered. The theoretical development of the meter is based on the energy model of electric machines in the form of differential equations for active and reactive power balance. This eliminates the direct influence of instability and nonlinearity of inductive elements and takes into account electrical, magnetic, mechanical, and harmonic losses using the simplest algorithms. Key variables of the model in the form of total active power and angular velocity are measured directly, and the high nominal efficiency of traction machines (95%) provides a wide tolerance range for calculating total losses. The information support of the meter is based on the traditional equipment of the traction electric drive, supplemented by voltage sensors of the three-phase inverter circuit. Accuracy characteristics of the meter are predicted under the assumption that the reduced torque measurement error does not exceed (2.5…3.0)% with an error of current, voltage, and speed measuring transducers of 1.5%. A tolerance range of (35…40)% determined for total losses satisfies the accepted conditions. Problems of adapting the meter to the technical characteristics and operating modes of traction machines are considered. Direct torque control algorithms have less accuracy.

The concept of using an electronic meter in a closed control system of a traction electric drive with torque feedback is considered. The purpose of this proposal is to improve the accuracy of torque control to the level of an electronic meter.
Development of a Light Weight Luggage Board Using the Sandwich Molding Method
Authors: Park Hee Sang , Yoon Yeon Sim , Lee Sr Seung Kun , Kim Sr Seok Cheol , Lee Dong Han
Published: April 2024

A crucial component utilized in the trunk space is the luggage board. Positioned at the bottom of the trunk, the trunk board separates the vehicle body from the interior and supports for luggage. The luggage board serves multiple functions, including load-bearing stiffness for luggage, partition structure functionality, noise insulation, and thermal insulation. There is a need for a competitive new luggage board manufacturing method to meet the increasing demand for luggage boards in response to the changing market environment. To address this, the "integrated sandwich molding method" is required. The integrated sandwich molding method utilizes three key methodologies: grouping processes to integrate similar functions, analyzing materials to replace them with suitable alternatives, and overcoming any lacking functionality through integrated design structures. This paper presents a methodology for developing the integrated sandwich molding method. It aims to validate the key performance aspects (stiffness, NVH, insulation) of trunk boards manufactured using this method, demonstrating productivity improvement and lightweight capabilities.
Road Recognition Technology Based on Intelligent Tire System Equipped with Three-Axis Accelerometer
Authors: Han Zongzhi , Liu Weidong , Liu Dayu , Gao Zhenhai , Zhao Yang
Published: April 2024

Under complex and extreme operating conditions, the road adhesion coefficient emerges as a critical state parameter for tire force analysis and vehicle dynamics control. In contrast to model-based estimation methods, intelligent tire technology enables the real-time feedback of tire-road interaction information to the vehicle control system. This paper proposes an approach that integrates intelligent tire systems with machine learning to acquire precise road adhesion coefficients for vehicles. Firstly, taking into account the driving conditions, sensor selection is conducted to develop an intelligent tire hardware acquisition system based on MEMS (Micro-Electro-Mechanical Systems) three-axis acceleration sensors, utilizing a simplified hardware structure and wireless transmission mode. Secondly, through the collection of real vehicle experiment data on different road surfaces, a dataset is gathered for machine learning training. This dataset is subsequently analyzed to discern the tire-ground relationships and signal characteristics. Finally, the utilization of a MiniRocket model, which employs binary multiple convolutional kernels to efficiently extract multiple signal features and enhance computational efficiency, facilitates feature learning from acceleration time-series data. By comparing the training results with other neural network models, the effectiveness, accuracy, and adaptability of the proposed MiniRocket neural network model for road surface recognition are comprehensively validated, even with limited training data. The road surface recognition solution presented in this paper successfully achieves real-time road identification. The seamlessly integrated hardware, software architecture, and neural network model are well-suited for vehicle system integration, providing real-time and precise road surface information for improved vehicle motion control.
Optimization of Mount Bracket on Whine Noise Performance for a Battery Electric Vehicle
Authors: Ding Chao , Jiang Xiaodong , He Weikang , Yu Huiqiang , Ma Yan
Published: April 2024

Recently, the market share of electric vehicles is becoming increasingly obvious. It is expected that electric vehicles are quieter than fuel vehicles. Actually, without the cover of low-frequency engine noise, the high-frequency noise of electric vehicles is more prominent, which seriously affect the perceived sound quality. The present work is related tonal noise resulted from electric drive system (EDS), which is one of the fundamental noise sources for battery electric vehicle (BEV). The dominant noise sources observed in the vehicle interior are 26th and 36th orders for reducer and drive motor separately. Poor vibration isolation of right mounting system is the fundamental cause identification of EDS noise which has been investigated with objective measurements and simulation tools. Dynamic stiffness analysis is carried out to optimize the passive bracket. An engineering solution is implemented to enhance bracket to improve resonance effect. The test results after improvement scheme has a 10dB(A) noise reduction for the whine noise of vehicle interior.
A Novel Torque Distribution Approach of Four-Wheel Independent-Drive Electric Vehicles for Improving Handling and Energy Efficiency
Authors: Dou Jingyang , Chen Zixuan , Zhang Yunqing , Wu Jinglai
Published: April 2024

This paper presents a torque distribution strategy for four-wheel independent drive electric vehicles (4WIDEVs) to achieve both handling stability and energy efficiency. The strategy is based on the dynamic adjustment of two optimization objectives. Firstly, a 2DOF vehicle model is employed to define the stability control objective for Direct Yaw moment Control (DYC). The upper-layer controller, designed using Linear Quadratic Regulator (LQR), is responsible for tracking the target yaw rate and target sideslip angle. Secondly, the lower-layer torque distribution strategy is established by optimizing the tire load rate and motor energy consumption for dynamic adjustment. To regulate the weights of the optimization targets, stability and energy efficiency allocation coefficient is introduced. Simulation results of double lane change and split μ road conditions are used to demonstrate the effectiveness of the proposed DYC controller.
An advanced tire modeling methodology considering road roughness for chassis control system development
Authors: Kim Changsu , O'Neill Alexander , Lugaro Carlo
Published: April 2024

As the automotive industry accelerates its virtual engineering capabilities, there is a growing requirement for increased accuracy across a broad range of vehicle simulations. Regarding control system development, utilizing vehicle simulations to conduct ‘pre-tuning’ activities can significantly reduce time and costs. However, achieving an accurate prediction of, e.g., stopping distance, requires accurate tire modeling. The Magic Formula tire model is often used to effectively model the tire response within vehicle dynamics simulations. However, such models often: i) represent the tire driving on sandpaper; and ii) do not accurately capture the transient response over a wide slip range. In this paper, a novel methodology is developed using the MF-Tyre/MF-Swift tire model to enhance the accuracy of ABS braking simulations. The methodology – developed between Hyundai Motor Company and Siemens Digital Industries Software – is validated on a full-vehicle level by comparing ABS braking simulations of ‘sandpaper’, ‘asphalt’, and ‘translated asphalt’ tire models against full-vehicle measurements, where friction modeling provided a way to translate sandpaper tire models to represent tires on asphalt. Results show a much-improved correlation of the asphalt-based simulations with vehicle measurements compared with flat-trac-based simulations. Thus, the methodology provides a suitable tire model for ABS braking simulations in the early stages of vehicle development without requiring physical vehicle tests.
Estimation of Poroelastic Material Properties of Noise Control Treatments Using Model Order Reduction
Authors: Salvekar Pinak , Raveendra Chris
Published: April 2024

Noise reduction is generally accomplished by applying appropriate noise control treatments at strategic locations. Noise control treatments consisting of poroelastic materials in layers are extensively used in noise control products. Sound propagation through poroelastic materials is governed by macroscopic material and geometric properties. Thus, a knowledge of material properties is important to improve the acoustical performance of the resulting noise control products. Since the direct measurement of these properties is cumbersome, these have been usually estimated indirectly from easily measurable acoustic performance metrics such as normal incidence sound transmission and/or absorption coefficient, measured using readily available impedance tube. The existing inverse characterization approaches fulfilled the estimation by curve fitting measured and predicted acoustic models. In this paper, in addition to the use of diffuse field performance metrics, a data driven machine learning approach is utilized to derive reduced order models. The properties of porous material are efficiently estimated by combining genetic algorithm with reduced order models. This approach is especially attractive to material suppliers, who usually lack information about material properties to improve their products.
Analysis and Improvement of the Cabin Low Frequency Noise Caused by Underbody Rear Cavity Airflow Oscillation in the Pure Electric Vehicle High Speed Cruise
Authors: Shen Long , Zhang Jun , Gu Perry
Published: April 2024

During the pure electric vehicle high speed cruise driving condition, the unsteady air flow in the chassis cavity is susceptible to self-sustaining oscillations phenomenon. And the aerodynamic oscillation excitation could be coupled with the cabin interior acoustic mode through the body pressure relief vent, the low frequency booming noise may occur and seriously reduces the driving comfort.

This paper systematically introduces the characteristics identification and the troubleshooting process of the low frequency aerodynamic noise case. Firstly, combined with the characteristics of the subjective jury evaluation and objective measurement, the acoustic wind tunnel test restores the cabin booming phenomenon. The specific test procedure is proposed to separate the noise excitation source.

Secondly, according to the road test results, it is inferenced that the formation mechanism of low frequency noise is the self- sustaining oscillation with the underbody shedding vortex feedback enhancement mechanism at the bottom of the rear chassis. The low frequency exterior airflow oscillation is coupled with the interior cabin acoustic modality by the two air relief vents located at the vehicle rear body parts.

Furtherly, the modal coupling mechanism is verified by the volumetric acoustic source excitation test in the semi-anechoic chamber. Considering the engineering feasibility and cost, some improvement schemes are proposed and verified by comparison. Finally, the cover of the vehicle body pressure relief vent is determined to the actual application, the cabin noise level in the specific low frequency band is reduced by 10 dB(A).

This paper provides a guiding reference for solving the similar low frequency noise problem of electric vehicles at the high-speed cruise condition.
Parameter Identification of Hyper-Elastic Model Based on Improved PSO-BPNN
Authors: Sun Jiawei , Zhao Renfei , Sun Hongjie , Ma Qiang
Published: April 2024

Rubber mount as an important element can reduce the vibration transmitted by the engine to the frame. And under small and medium deformation conditions, Mooney-Rivlin model can well describe the mechanical properties of the rubber mount. The accurate parameters of Mooney-Rivlin model are the basis of describing the mechanical properties of the mount. First, taking powertrain rubber mount as the research object, the influence of preload on the static characteristics of the mount is studied by the preload test rig. Second, Particle swarm optimization-Back propagation neural network (PSO-BPNN) model and Back propagation neural network (BPNN) model was established. After the number and step length of hidden layer neurons were determined, the prediction accuracy of the two models is compared. Then, combined with finite element analysis and crow search algorithm, a parameter identification model considering preload is established, the constitutive parameters corresponding to preload and non-preload conditions are identified, and the influence of multi-axial load on the identification of constitutive parameters is studied. The results show that: The prediction accuracy and stability of PSO-BPNN model are higher than that of BPNN model. Compared with the constitutive parameters corresponding to the non-preload conditions, the errors of X and Y calculated according to the constitutive parameters identified under the preload conditions are significantly reduced in each working condition, and the errors of each working condition in the three directions are within 15%, which can more accurately describe the mechanical properties of the rubber mount under each working condition.
Elucidation of Sealing Mechanism of Novel Acrylate Liquid Based BluSeal
TM
Wire Harness Splice Sealing Technology
Authors: Chung Dennis
Published: April 2024

Unlike conventional heat shrink tubes or enclosure systems which only seals wires and splices on the outside, a novel Acrylate based sealing technology developed and introduced by Eurotech is a low viscosity fluid formulated to be applied to the splices either in liquid droplets or by dipping, utilizes fast capillary-wicking action and quick self-cure inside the wires to form a robust, cost effective, flexible, impenetrable seal to prevent moisture damage of wire harnesses and associated electrical components. This technology is an enabler of new wire harness architectures currently limited by the shortcomings of conventional sealing products such as heat shrink tubes which come up short when the splice configurations or geometries become too complex or difficult for sealing from the outside.

Sealing mechanism investigation was launched and the results of the analytical experiments are presented to reveal how this unique sealing technology works to effectively withstand pneumatic air bubble pressure applied to the wires thus demonstrating effective prevention of water ingress into the wires. Surface energy analysis performed for this sealing liquid against metal and plastic surfaces is presented to confirm the capillary action observed within wires. Real-time FTIR data confirmed its fast cure kinetics which also supports the proposed hypothesis of the interfacial cure initiation and solid front growth phenomena inside the wires. Cross sectional microscopy and sealing depth profiling investigations point to the synergy of capillary action, fast cure kinetics combined with robust adhesive chemistry of this sealing system as primary contributors to achieving a durable, robust in-wire sealing capability of this technology. Automotive OEM performance specification test results for sealing performance and long-term durability of this technology are also presented.
Exploring Natural Frequency and Damping in Coir-Rubber Polymer Composites for Vibration Control in Mobility Vehicles
Authors: Mache Ashok , Kulkarni Aparna , Shah Swapnil , Gujar Adesh , Hujare Pravin
Published: April 2024

This study delves into the dynamic properties of hybrid composite materials, specifically focusing on the natural frequency and modal damping characteristics of Coir Fiber-Rubber Particles Reinforced Polymer Composites (CRP). Comprehensive experimental investigations were conducted utilizing an FFT analyzer. Initial experiments involved the preparation of specimens with varying rubber content, ranging from 2% to 5%. Coir, known for its cellulose-rich composition, was selected due to its innate damping properties, making it highly effective in mitigating vibrations. The primary motivation behind this research is to provide cost-effective solutions for reducing vibrations in mobility vehicles, addressing challenges associated with passenger comfort, durability, and overall performance. The study yielded promising results, with CRP exhibiting substantial reductions in vibrations. The findings of this research are expected to serve as valuable inputs for the design and engineering of components utilizing these novel composite materials. By characterizing the natural frequencies and damping properties, this study empowers engineers and designers with crucial insights for selecting appropriate materials to tackle vibration-related challenges in mobility vehicle applications.
Digital Cockpit in the Era of the Software-Defined Vehicle
Authors: Taylor Kyle
Published: April 2024

The next generation of digital cockpits requires modern architectures to be successful and affordable. This paper provides an in-depth view on the future of digital cockpit architectures. The currently emerging architectures are explored with two main points in focus: The key experiences that drive customer expectations and the options to cost-effectively meet those expectations—while keeping the vehicle affordable. Modern architectures rely on middleware services. Well-designed middleware services allow for an efficient and reusable approach across different model lines and market segments. The paper presents this approach. The new architectures also lead to a transformation of the partner ecosystem between original equipment manufacturers (OEMs) and component suppliers. OEMs try to lever this system while maintaining control over their offerings. These changes transform the traditional semiconductor industry as a whole. The reasons for this transformation and why it is necessary to meet the needs of a zonal architecture is examined. The paper finishes with a look at how cloud-based services and content can be incorporated while providing a unique brand experience.
The Effects of the Oil Temperature Warm-Up on Engine Fuel Consumption
Authors: Di Giovine Giammarco , Di Battista Davide , Cipollone Roberto
Published: April 2024

The need for even more efficient internal combustion engines in the road transportation sector is a mandatory step to reduce the related CO2 emissions. In fact, this sector impacts significantly on greenhouse gases worldwide, and the path toward hybrid and electric powertrains has just begun. In particular, in heavy-duty vehicles the full electrification of the powertrain is far to be considered as a really feasible alternative. So, internal combustion engines will still play a significant role in the near/medium future. Hence, technologies having a low cost to benefits (CO2 reduction) ratio will be favorably introduced in existing engines. Thermal management of engines is today a recognized area of research. Inside this area, the interest toward the lubricant oil has a great potential but not yet fully exploited. Engine oil is responsible of the mechanical efficiency of the engine which has a significant potential of improvement. A faster warm-up during a daily urban trip when the engine starts from a cold state is a good way to reduce fuel consumption (CO2 emissions) and also harmful emissions, which represent the most critical aspect in urban areas. Conventional oil warm-up takes several minutes to reach a thermal regime, during which inefficiencies related to the low oil temperature are significant.

In this paper, the relation between oil temperature and fuel consumption of a turbocharged diesel engine has been evaluated, matching a theoretical approach with experimental data. The oil warm-up has been registered during a homologation cycle when the engine was managed as light-duty propulsion system. Most part of the working conditions was done with the oil far from a thermal regime, demonstrating poor efficiency and high harmful emissions. Then, several strategies to speed up the oil warm-up have been investigated, characterizing the benefits in terms of CO2 emissions. Particularly, the use of a thermal storage available on board resulted effective, as well as an eventual heat recovery from exhaust gases which immediately reach a temperature level enough to heat up the oil.
Development and Application of Diagnosis Logic of Ion Exchange Filter Depletion
Authors: Jang Wook Il (Woogil) , Kim Seong-Mok
Published: April 2024

With the widespread adoption of fuel cell electric vehicles, electrical insulation resistance is required for driver safety. However, there are two ways in which resistance decreases: the first is electrical shorts because of failure of high-voltage components, and the second is increased conductivity of fuel cell coolant because of depletion of ion exchange filter. In the conventional solution, since these two decreases could not be distinguished due to noise in the resistance value, a vehicle alerted customers without determining the cause and severity when the resistance value falls below a certain threshold.

As a corrective maintenance, when an alert occurs, the vehicle is forced to be immediately delivered to the service center. However, in most cases where the alert came on, the cause was low-risk ion filter depletion. This resulted in customers complaining that they were startled and considering the alert to be non-threatening. As a result, the provider recommended customers to replace the ion exchange filter earlier than the recommended interval which results in an increase in maintenance cost.

Therefore, by developing diagnosis the depletion of the ion filter separately as a preventive maintenance and showing simple notice to customer in cluster, the alert can inform customers of only truly dangerous situations, increasing trust in the warning and maximizing the usage of ion filters. To address the limitations of conventional approaches, this paper presents the world's first technique for diagnosis of depletion of ion exchange filters based on pattern recognition of insulation resistance data with high accuracy and noise avoidance. Using driving data from fuel cell electric vehicles, such as the NEXO, this paper demonstrates that the proposed diagnosis logic can detect ion filter depletion with an accuracy of 99.3% (3,093/3,115) for Type I errors and 85.9% (269/313) for Type II errors.

By adopting this proposed diagnosis, it is possible to extend the usage period of ion exchange filters and enhance customer convenience, maintenance cost and environmental sustainability. Since eco-friendly cars have many chemical parts (batteries, fuel cell stacks, etc.) that gradually deteriorate, such as ion filters, research on these diagnosis technologies is expected to continue to expand. The diagnosis logic would be updated to Hyundai-Kia Motors' 2nd-generation fuel cell electric vehicles (including NEXO), and for vehicles after the 3rd generation, the diagnosis logic would be basically applied.
Impact of Advanced Technologies on Energy Consumption of Advanced Electrified Medium-Duty Vehicles
Authors: Kim Namdoo , Islam Ehsan Sabri , Vijayagopal Ram
Published: April 2024

The National Highway Traffic Safety Administration (NHTSA) has been leading U.S. efforts related to the rulemaking process for Corporate Average Fuel Economy (CAFE) standards. Argonne National Laboratory, a U.S. Department of Energy (DOE) national laboratory, has developed a full-vehicle simulation tool called Autonomie that has become one of the industry standard tools for analyzing vehicle performance, energy consumption, and technology effectiveness. Through an Interagency Agreement, the DOE Argonne Site Office and Argonne National Laboratory have been tasked with conducting full vehicle simulation to support NHTSA CAFE rulemaking.

This paper presents an innovative approach focused on large-scale simulation processes spanning standard regulatory driving cycles, diverse vehicle classes, and various timeframes. A key element of this approach is Autonomie’s capacity to integrate advanced engine technologies tailored to specific vehicle classes and powertrains. By customizing simulations to replicate real-world conditions for different vehicle types, this research provides nuanced insights essential for the development and implementation of effective CAFE standards.

Our CAFE analysis encompassed simulation of more than 10,000 vehicle combinations across different heavy-duty pickup and van classes. The wide range of vehicle combinations we analyzed included electrified powertrains combined with various component performance scenarios. This paper details Argonne’s investigation into the performance and energy consumption of electrified powertrains simulated for the NHTSA’s Notice of Proposed Rulemaking published in 2023.
Lightweight Design Enabled by Innovative CAE Based Development Method Using Topology Optimization
Authors: Kato Yoshiya , Ishikawa Satoru , Puchner Klaus , Schossleitner Martin , Gaier Christian
Published: April 2024

Carbon neutrality has become a significant target. One essential parameter regarding energy consumption and emissions is the mass of vehicles. Lightweight design improves the result of vehicle life cycle assessment (LCA), increases efficiency, and can be a step towards sustainability and CO2 neutrality. Weight reduction through structural optimization is a challenging task. Typical design development procedures have to be overcome. Instead of just a facelift or the creation of a derivative of the predecessor design, completely alternative design creation methods have to be applied. Automated structural optimization is one tool for exploring completely new design approaches. Different methods are available and weight reduction is the focus of topology optimization. This paper describes a fatigue life homogenization method that enables the weight reduction of vehicle parts. The applied CAE process combines fatigue life prediction and topology optimization. An adapted design for a differential case was found, which does not sacrifice strength or stiffness properties of the component. Despite the very limited freedom for design modification, an interesting solution that saves nearly 20% of mass could be obtained, which demonstrates the potential of this approach to help achieve carbon neutrality through material saving. Other properties such as bolt loosening, stiffness, and castability were also considered. Verification with finite element analysis, fatigue assessment, and testing of the original and optimized components were performed. The lifetime results for virtual and real testing match quite closely and prove the effectiveness of this fatigue life homogenization method. Fine tuning of the simulation was also performed. Local material characteristics were considered based on filling and solidification simulations for the cast process of the component.
Design Optimization of a Lightweight Electric Bus Body Frame Orienting the Static Performance and Side-Impact Safety
Authors: Yang Xiujian , Tian Dekuan
Published: April 2024

This work aims to perform the optimization of the iron-aluminum lightweight body frame of a commercial electric bus orienting the static performance (e.g., strength and stiffness), side-impact safety, and possible reduction in mass. Firstly, both the static and side-impact finite element (FE) models are established for the electric bus body frame. The body frame is partitioned according to the deformation and the thickness of the square tube beams, and the contribution is analyzed by the relative sensitivity and the Sobol index methods. The thickness of the tube beams in the nine regions is selected as the design optimization variables. After data sampling by the Hamersley method and conducting design of experiments (DOE), the surrogate models for optimization are fitted by the least square method. A multi-objective optimization problem is formulated by selecting the mass of the overall body frame, the maximum vehicle stress and the intrusion of the upper part of the collision area as the objectives of design optimization. The optimization problem is solved by the co-evolutionary constrained multi-objective optimization algorithm. By respectively focusing more on each of the three optimization objectives, three optimization schemes are solved and discussed. The optimization results are finally evaluated by FE simulations, and it is revealed that the stress is reduced by 34.41% and the side-impact intrusion is reduced by 4.48%, while the vehicle mass remained basically unchanged. The proposed optimization method can effectively improve the static performance and the side-impact performance of the iron-aluminum lightweight electric bus body skeleton.
Front Bumper Dive During Maximum Braking of ABS-Equipped Vehicles
Authors: Young Steven , Gish Russell , Siegmund Gunter P.
Published: April 2024

Passenger vehicle bumpers are designed to reduce collision damage. If colliding bumpers are not vertically aligned, their effectiveness is reduced and the resulting damage increases. Two bumpers of similar static design heights may become misaligned due to bumper dive caused by one or both vehicles pitching forward due to braking. Previous researchers have quantified bumper dive and how it changed with passenger vehicle designs. Currently there are limited data available to quantify the mean, variance, and distribution of bumper dive for modern ABS-equipped vehicles. We conducted maximum braking tests using 3 late-model minivans/CUVs (crossover utility vehicles) and 9 late-model sedans on contiguous dry asphalt and concrete road surfaces. Between 16 and 23 tests were conducted for each vehicle and all tests were conducted from an initial speed of about 65 km/h (40 mph). A laser distance sensor mounted to the front bumpers measured bumper height throughout each test. Overall, we found the average maximum front bumper dive of late-model minivans/CUVs varied from 7.8 to 9.1 cm (3.1 to 3.6 in) and the front bumper dive of late-model sedans varied from 4.3 to 6.3 cm (1.7 to 2.5 in). Steady-state dive was 3 mm (0.1 in) greater when braking on asphalt compared to concrete, but this difference was small compared to the variance observed between tests.
Accuracy of Rectifying Oblique Images to Planar and Non-Planar Surfaces
Authors: Hashemian Alireza , Terpstra Toby
Published: April 2024

Emergency personnel and first responders have the opportunity to document crash scenes while evidence is still recent. The growth of the drone market and the efficiency of documentation with drones has led to an increasing prevalence of aerial photography for incident sites. These photographs are generally of high resolution and contain valuable information including roadway evidence such as tire marks, gouge marks, debris fields, and vehicle rest positions. Being able to accurately map the captured evidence visible in the photographs is a key process in creating a scaled crash-scene diagram. Image rectification serves as a quick and straightforward method for producing a scaled diagram. This study evaluates the precision of the photo rectification process under diverse roadway geometry conditions and varying camera incidence angles.
Scenario-Based Development and Meta-Level Design for Automotive Systems: An Explanatory Study
Authors: Knödler Julian , Muhl Philip , Sax Eric , Eckstein Lutz
Published: April 2024

Prevailing automotive development focus shifts towards passenger-centric development of vehicle systems. Comparative to autonomous driving development, the challenge evolves to describe all relevant driving situations with the necessary information and context to be able to develop and optimize vehicle systems to actual driving situations. The situational description or scenario, i.e., context or ambiance in which a vehicle is located, represents a fundamental factor in consideration of system behavior and respective system optimization opportunities. The challenge to solve the respective automotive engineering problems for nonlinear multidimensional parameter spaces or mixed integer classification problems is to describe and limit the possible solution space by suitable methodologies. Conventional methods prove inadequate solution as they can only be applied with significant financial resources and engineering time efforts, as known by autonomous driving system development. A key requirement is to reduce the necessity of various concrete scenarios of possible parameter combinations and situation states, in which the vehicle systems operate. We adapt methods to describe driving situations similarly in the context of autonomous driving and derive commonalities for generic application in the context of vehicle development. We discuss our derived and extended approach using two technical case studies from the engineering domains of thermal management as well as energy prediction and point out limitations and pitfalls in application. Conclusively, we present our view on further challenges and opportunities by applying our method in the automotive context and what opportunities arise with our scenario description methodology.
CAATS – Automotive Wind Tunnel Statistical Process Control
Authors: Bringhurst Katlynn , Walter Joel , Best Scott
Published: April 2024

This paper presents the application of statistical process control (SPC) methods to Windshear, a 180-mph motorsports and automotive wind tunnel equipped with a wide-belt rolling road system. The SPC approach captures the complete variability of the facility and offers useful process performance metrics that are based on a sound statistical framework. Traditional control charts are explored, emphasizing the uniqueness of variability experienced in wind tunnels which includes significant, unexplained short-term and long-term variation compared to typical manufacturing processes. This unique variation is elegantly captured by the three-way control chart, which is applied to estimate the complete process reproducibility with different levels of repeatability of vehicle drag coefficient. The sensitivity of three-way control charts is explored including the evaluation of an alternate group assignment within the same dataset. A practical example is provided evaluating secondary boundary layer fan performance after a failure event to demonstrate the effectiveness of three-way control charts in establishing and maintaining a rigorous automotive wind tunnel maintenance program. SPC charts and their resultant analysis are a function of the test matrix that generates them. The development of a rigorous SPC test matrix is discussed including an example provided by Windshear. This paper is part of a global effort to Commonize Automotive Aerodynamic Testing Standards (CAATS) launched by the Subsonic Aerodynamic Testing Association (SATA).
A methodology for modeling the thermal behavior of an electric axle in real driving cycles
Authors: Hu Xiaoyu , Shao Hengheng , Hou Yuanjing , Sun Wanyu , Liu Hongwei , Zhang Lin
Published: April 2024

The thermal behavior of the electric axle is an essential indicator which requires certain attention during the development process. Due to the complexity of heat generation mechanism and heat transfer boundary conditions, it is difficult to accurately predict the axle’s temperature, especially in real driving conditions. In this paper, a comprehensive 1D model is developed to simulate its heat transfer process effectively and accurately.

The heat transfer model is developed based on the thermal network method, and the electric axle is divided into thermal mass according to its heat transfer characteristics. The heat generation model, which accounts for meshing loss, bearing loss, churning loss, and windage loss, exchanges heat flux and oil temperature information with the heat transfer model to take into account the effect of lubricating oil temperature on power loss. Meanwhile, 3D simulation is established for the lubricating oil flow inside the axle and the air flow around it, from which the fluid velocity or void fraction could be generated and further applied to calculate the heat transfer coefficient. Thus, the integrated 1D model is realized to simulate the whole heat transfer process.

The proposed model is validated under several real driving cycles of a commercial heavy-duty truck, and the simulation results show positive consistency with experimental results. Further analysis is conducted including proportion of various power loss and oil temperature rise curve, which provides profound insight into understanding thermal behavior of the electric axle. In conclusion, the proposed method exhibits attractive application prospect in the design and optimization process.
Multidisciplinary Design Method for Off-Road Vehicles Using Bayesian Active Learning
Authors: Kawamura Hiroaki , Haruki Misuzu , Toyoda Hiroyuki , Shintani Kohei
Published: April 2024

When developing an off-road vehicle, it is essential to create excellent drivability that enables the vehicle to be driven on all surfaces while ensuring passenger comfort. Since durability is another indispensable performance aspect for these vehicles, the development method must be capable of considering a high-level combination of a wide range of performance targets. This paper proposes a method to identify the region in which each performance aspect is realized through a complex domain combination problem. The proposed method is helpful in the initial design stage when the detailed specifications of the target vehicle are not determined because it is capable of considering both the specifications and usage method of the target vehicle, such as the selection of road profiles and driving speeds as design variables. The proposed method has the advantage of enabling efficient concurrent studies to search for feasible regions. By introducing a probabilistic representation of multidisciplinary constraint functions, the feasible regions of each discipline subproblem can be decoupled by the rule of product. This nature makes adding the constraint functions in the later design stage easy. In contrast, it is unclear which constraint function is active at the early design stage. Calculating inactive constraint functions yields a complex prediction model and requires a higher calculation cost. In the early stage of off-road vehicle design, many design variables and unclear cost functions exist. This paper proposes an improved modeling method represented as the combination of constraint functions. The proposed method can deal with more complex constraint functions without degradation of model accuracy. To show the effectiveness of the proposed method, a practical numerical example of a multidisciplinary vehicle design problem is presented.
Technical Challenges with on Board Monitoring
Authors: Funk Sarah , Potter Janean , Pruski Erika
Published: April 2024

The proposed Euro 7 regulation includes On Board Monitoring, or OBM, to continuously monitor vehicles for emission exceedances. OBM relies on feedback from existing or additional sensors to identify high emitting vehicles, which poses many challenges. Currently, sensors are not commercially available for all emissions constituents, and the accuracy of available sensors is not capable enough for in use compliance determination. On board emissions models do not offer enough fidelity to determine in use compliance and require new complex model innovation development which will be extremely complicated to implement on board the vehicle. The stack up of multi-component deterioration leading to an emissions exceedance is infeasible to detect using available sensors and models. An assessment of limitations and measurement accuracy for sensors or models including oxides of nitrogen (NOx) sensors under a variety of operating conditions, ammonia (NH3) sensing, and particulate matter (PM) sensing is provided. This paper also reviews what is being promulgated elsewhere in regard to using on-board sensors or portable emissions measurement systems (PEMS) to directly measure pollutants such as the California Air Resources Board (CARB) “Real Emissions Assessment Logging (REAL) NOx Tracking” system and in-use on-road emissions testing requirements. Considering the aforementioned technical challenges with OBM, we will offer practical measures to identify significant excess emissions and detect tampering of the emission system. We will consider the use of already available designs including statistical analysis of diagnostic results and other solutions that can be implemented quickly. One such solution is closing the gap to existing US/CARB On Board Diagnostic (OBD) requirements. We will also discuss the challenges of defining standardized data parameters to support the proposed implementation timing.