bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study on the Development of Concept Models Using Higher-Order Beams
Authors: Kim Jin Hong , Lee Dong Ki , Kim Gyu Sik , Jang Gang-Won , Kim Han Kil
Published: April 2024

In the early stages of vehicle development, it is critical to establish performance goals for the major systems. The fundamental modes of body and chassis frames are typically assessed using FE models that are discretized using shell elements. However, the use of the shell-based FE method is problematic in terms of fast analysis and quick decision-making, especially during the concept phase of a vehicle design because it takes much time and effort for detailed modeling. To overcome this weakness, a one-dimensional (1D) method based on beam elements has been extensively studied over several decades, but it was not successful because of low accuracy for thin-walled beam structures. This investigation proposes a 1D method based on thin-walled beam theory with comparable accuracy to shell models. Most body pillars and chassis frame members are composed of thin-walled beam structures because of the high stiffness-to-mass ratio of thin-walled cross sections. However, thin-walled cross-sections are also vulnerable to sectional deformations in out-of-plane and in-plane directions, called warping and distortion, respectively. The proposed higher-order beam elements employ these sectional deformations as additional degrees of freedom. The validity of the proposed method is verified by solving the frame and body structures of a vehicle, whose results are compared with those of shell models. Furthermore, we develop a pre/post-processing program for higher-order beam analysis. Through this program, we can save significant time and effort in not only building higher-order beam models but also conducting sensitivity analysis for various variations.
Virtual Simulation and Design Optimization of Bi-Functional Projector Headlamp for Nighttime Visibility of Overhead Signs
Authors: Yadav Prashant Maruti
Published: April 2024

For safe driving function, signs must be visible. Sign visibility is function of its luminance intensity. During day, due to ambient light conditions sign luminance is not a major concern. But during night, due to absence of sun light sign board retro-reflectivity plays a crucial role in sign visibility. The vehicle headlamp color, beam pattern, lamp installation position, the relative seating position of driver and moon light conditions are important factors. Virtual simulation approach is used for analyzing the sign board visibility. Among various factors for example the headlamp installation position from ground, distance between two lamps and eye position of driver are considered for analyzing the sign board visibility in this paper. Many automotive organizations have widely varying requirements and established testing guidelines to ensure visibility of signs in head lamp physical testing but there are no guidelines during design stage for headlamp for sign visibility.

In this paper, among several other considerations focus is given on enhancing the driver’s ability to truly control the driving experience using Ansys VRXperience night drive simulator capability. Bifunctional LED projector headlamp CAD is used for generating light intensity files in Lucid Shape. These light intensity ray files (IES file format) which is output from Lucid Shape software is used as input to Ansys VRXperience for in scenario driving simulation and to understand the real time visibility of signs while driving. The nighttime sign visibility simulation process is established for virtual verification of lamp installation position and consequently its impact on driving experience in early design phase. This helps in addressing last minute changes in design and costly prototype mockups required to check the safety aspect.
A New Equation for Modeling S-N data of Steels
Authors: Huang Gang
Published: April 2024

High cycle fatigue (HCF) S-N curves of steels are applied by OEMs for direct evaluation of the products' durability or as an input to their CAE for design purpose. It has been found that the existing models for S-N data resulting HCF test might have difficulties in properly depicting the entire spectrum of fatigue lives. To overcome these difficulties, a new equation has been developed based on the relationship between the behaviors of short and long fatigue lives. The new equation was applied to model S-N data resulting from recent HCF testing of several steels and was compared with the 3 existing popular models. The comparison in the preliminary validations indicated that the new equation has high potential for application in more accurate S-N data modeling and fatigue limit prediction.
Elucidation of Deteriorating Oil Consumption Mechanism Due to Piston Top Ring Groove Wear
Authors: Yoshii Kenta , Takahashi Katsuyuki , Sato Kenji , Hitosughi Hideshi , Nakada Fumihiro
Published: April 2024

The piston and piston ring are used in a severe contact environment in engine durability tests, which causes severe wear to the piston ring groove, leading to significant development costs for countermeasures. Conventionally, in order to ensure functional feasibility through wear on the piston top ring groove (hereinafter “ring groove”), only functional evaluations through actual engine durability testing were performed, and there was an issue in determining the limit value for the actual amount of wear itself. Because of this, the mechanism that may cause wear on the ring groove was clarified through past research, but this resulted in judgment criteria with some leeway from the perspective of functional assurance. To establish judgment criteria, it was necessary to understand both functional effect from ring groove wear and the mechanism behind it. For this research, the functional effect from wear on the upper surface of the ring groove and the mechanism that may cause this were clarified by performing two types of experiments. First, oil consumption tests were performed by incorporating a piston with a worn upper surface into an actual engine to confirm the functional effect from ring groove wear. The results showed that oil consumption deterioration and blow-by gas backflow occurred. Next, to clarify this phenomenon, uneven wear was simulated and a piston with additional machining was incorporated into a single-cylinder engine to compare piston ring motion on the thrust and anti-thrust side. Based on the results, it was confirmed that the piston ring does not sit on the upper surface of the groove on the anti-thrust side and that the blow-by gas flows back. The functional limit value and the allowance margin were grasped thanks to understanding the functional effect and the mechanism behind it, and the judgment criteria for wear amount was clarified, which enabled optimal design.
Application of Motor Load Emulation Techniques for EPB (Electric Parking Brake) System Tests
Authors: Son Changhyun , Yu Hyunuk
Published: April 2024

The EPB (Electric Parking Brake) system is divided into two parts based on VDA305-100 recommendation (German Association of the Automotive Industry, VDA). One part of the EPB system contains the parking brake actuator, caliper, and actuation logic (parking brake controller, PBC). The second part of the EPB system is called to the HOST which contains the EPB power electronics, necessary peripherals and controls the functions that the driver can experience.

According to VDA305-100, the PBC is responsible for recognition of a fault in the parking brake actuator based on the measured values transmitted from the HOST such as EPB motor voltage and current. Due to mechanical fault injection limitations, failsafe tests require physically electrical emulation caused by parking brake actuator faults to verify the parking brake actuator fault detection and management algorithm.

This paper introduces EPB motor load emulation techniques in which EPB HILS (Hardware in the Loop Simulation) test environment in real-time with simple DC (Direct Current) motor model and caliper model. The test environment can provide not only normal EPB actuation tests described in VDA305-100 recommendation but also dedicated failsafe tests of parking brake actuator stuck, stall, abnormal EPB actuation without a command from the HOST and abnormal EPB motor input voltage situation under various physically electrical emulation conditions.
Tire Force Estimation Using Intelligent Tire System Detecting Carcass Deformation
Authors: Wu Haidong , Wang Xiaopeng , Lu Dang
Published: April 2024

In this paper, an intelligent tire system is designed to estimate tire force by detecting the tire carcass deformation. The intelligent tire system includes a set of marker points on the inner liner of the tire to locate the position of tire carcass and a camera mounted on the rim to capture the position of these points under different driving conditions. An image recognition program is used to identify the coordinates of the marker points in order to determine the deformation of the tire carcass. According to the tire carcass stiffness test and the general tire carcass deformation theory, an approximate linear relationship between tire force and carcass deformation in all directions was obtained. The vertical force of the tire is determined by the distance between adjacent marker points. The longitudinal force and lateral force of the tire are estimated by measuring the longitudinal and lateral displacements of the marker points. The innovation of this paper lies in the use of image recognition techniques to quantify the deformation of the tire carcass and the estimation of the tire force based on the relationship between the carcass deformation and the tire force which is considered to be linear. The steady-state tire characteristic tests under different input conditions are designed and the tire six component force is collected. The effectiveness of the designed intelligent tire system is investigated by comparing the experimental results with the intelligent tire system estimation results, and the results show that the system has good tire force estimation accuracy under both pure slip and combined slip conditions.
Fitting Laplace Process Parameters for Non-equidistant Road Roughness Data
Authors: Speckert Michael , Dahlheimer Thorsten , Fiedler Jochen
Published: April 2024

Road roughness is the most important source of vertical loads for road vehicles. To capture this during durability engineering, various mathematical models for describing road profiles have been developed. The Laplace process has turned out to be a suitable model, which can describe road profiles in a more flexible way than e.g., Gaussian processes. The Laplace model essentially contains two parameters called C and ν (to be explained below), which need to be adapted to represent a road with certain roughness properties. Usually, local road authorities provide such properties along a road on sections of constant length, say, 100 m. Often the ISO 8608 roughness coefficient or the IRI (International Roughness Index) are used. In such cases, there are well known explicit formulas for finding the parameters C and ν of the Laplace process, which best fits the road under certain assumptions. Besides local road authorities there are also other sources of roughness data, for instance commercial providers of digital maps. Sometimes, the information is given for road sections of varying length such that these formulas do not apply anymore. Therefore, this paper suggests a method to fit the Laplace parameters in the more general setting of non-equidistant roughness data. Neither the roughness indicators nor the Laplace model are modified, just the process of parameter fitting is adapted. The task is reduced to solving a maximum-likelihood problem. In addition, an explicit formula approximating the maximum-likelihood solution for the Laplace parameters C and ν is derived. This extends the explicit formulas known for data on an equidistant grid. The methods and results are validated based on roughness data for roads of a total length of 1270 km. Road surface properties are also highly relevant for vehicle vibration, ride comfort, or handling. However, this is not considered further in this paper.
Gap Adjustment Strategy for Electromechanical Brake System Based on Critical Point Identification
Authors: Zhang Yilong , Chen Zixuan , Wu Jinglai , Zhang Yunqing
Published: April 2024

Abrasion of the Electromechanical brake (EMB) brake pad during the braking process leads to an increase in brake gap, which adversely affects braking performance. Therefore, it is imperative to promptly detect brake pad abrasion and adjust the brake gap accordingly. However, the addition of extra gap adjustment or sensor detection devices will bring extra size and cost to the brake system. In this study, we propose an innovative EMB gap active adjustment strategy by employing modeling and analysis of the braking process. This strategy involves identifying the contact and separation points of the braking process based on the differential current signal. Theoretical analysis and simulation results demonstrate that this gap adjustment strategy can effectively regulate the brake gap, mitigate the adverse effects of brake disk abrasion, and notably reduce the response time of the braking force output. Monitoring is critical to accurately control EMB clamping force. Pressure transducers are often expensive and have limited accuracy in high-temperature environments, so an estimate of the clamping force is required. In this research, the clamping force is estimated based on the identified contact points and the stiffness profile of the EMB. This method performs exceptionally well under low stiffness conditions and maintains a narrow error range even in high-stiffness scenarios.
A Precise Clamping Force Control Strategy for Electro-Mechanical Braking System Based on Nonlinear Characteristics Compensation
Authors: Jin Xin , Wu Jian , Zhang Yufan , Zhao HuiChao , Zhao Yongqiang , Yu Zhen , Chen Zhicheng
Published: April 2024

Electro-Mechanical Braking (EMB) system, which completely abandons the traditional hydraulic device, realizes complete human-vehicle decoupling and integrates various functions without adding additional accessories, could meet the requirements of the future intelligent driving technology for high-quality braking control. However, there are significant internal interference of nonlinear characteristics such as mechanical friction and system variable stiffness during the actual working process of EMB, and these make the accuracy and rate of the clamping force control decline. This paper proposes a precise clamping force control strategy for EMB based on nonlinear characteristics compensation. First, we systematically analyze the working principle of EMB, and establish the mathematical model of EMB system including motor, transmission mechanism and friction. At the same time, some typical experiments are designed to identify internal parameters of friction model. Next, in order to establish the precise clamping force control for EMB, we apply the Proportional-Integral (PI) theory to a clamping force-speed-current cascade controller. Considering simple PI theory is difficult to overcome the nonlinear characteristics faced by EMB in the clamping force control process, the inverse gain function linearization and load feedforward compensation are utilized to deal with the variable stiffness characteristics of the EMB system. On this basis, we jointly use identified friction model to dynamically compensate EMB nonlinear characteristic interference. Finally, we construct a hardware-in-the-loop (HiL) platform based on dSPACE to compare the designed strategy with traditional clamping force control method. The test results demonstrate the designed strategy could more effectively overcome the interference of EMB nonlinear characteristics, and significantly improve the rate and accuracy of clamping force control.
Maximum Curve-Passing Speed Correction for Online Trajectory Optimization of Autonomous Vehicles
Authors: Lou Baichuan , Zhao Bolin , He Xiangkun , Ren Dongchun , Lv Chen
Published: April 2024

In emergency circumstances, it is essential for autonomous vehicles to balance stability and dynamic performance to attain a faster travel speed while preserving stability. It is not unusual to find traffic accidents caused by suddenly present intruders on the road. In this situation, if there is not enough distance for the vehicle to brake immediately, the vehicle needs to operate with a relatively big steering angle and cornering speed to avoid collision while maintaining driving stability. This can be a challenging scenario even for a human driver, let alone autonomous driving. Especially, this poses a burden on trajectory optimization. In this case, neither over-conservative nor unachievable trajectory and speed profiles are eligible. Technically, the difficulty lies in an accurate maximum cornering speed estimation due to the impact of nonlinear tire force responses in these scenarios with large steering angles and high cornering speed. While this difficulty can be addressed by introducing tire model and extra variables, like tire stiffness and shape factor, in the formulation of this problem to cover nonlinear effect, it ends up increasing the complexity of the model and optimization problem. In this paper, a novel maximum curve-passing speed correction method for online trajectory optimization is proposed by leveraging predefined nonlinear correction terms, which is applicable without introducing any extra variables to the optimization. Moreover, this method has been simulated in the autonomous vehicle software-in-the-loop system. It is validated that this method can achieve online trajectory planning with maximum curve-passing speed while ensuring lateral stability.
Data-Enabled Human-Machine Cooperative Driving Decoupled from Various Driver Steering Characteristics and Vehicle Dynamics
Authors: Guo Hongyan , Shi Wanqing , Zhang Jiaming , Liu Jun
Published: April 2024

Human driving behavior's inherent variability, randomness, individual differences, and dynamic vehicle-road situations give human-machine cooperative (HMC) driving considerable uncertainty, which affects the applicability and effectiveness of HMC control in complex scenes. To overcome this challenge, we present a novel data-enabled game output regulation approach for HMC driving. Firstly, a global human-vehicle-road (HVR) model is established considering the varied driver's steering characteristic parameters, such as delay time, preview time, and steering gain, as well as the uncertainty of tire cornering stiffness and variable road curvature disturbance. The robust output regulation theory has been employed to ensure the global DVR system's closed-loop stability, asymptotic tracking, and disturbance rejection, even with an unknown driver's internal state. Secondly, an interactive shared steering controller has been designed to provide personalized driving assistance. Two control subsystems, active front-wheel steering (AFS) and active rear-wheel steering (ARS) systems, are emulated as a dynamic non-zero-sum game to explore a more flexible balance between the dual objectives of path-tracking accuracy and vehicle stability. Finally, the control policy iterative equalities of the AFS and ARS systems are constructed utilizing the coupled game Riccati equation and Kronecker product. Adaptive dynamic programming (ADP) has been employed to iteratively update and learn the optimal shared strategy without relying on accurate knowledge of driver steering characteristics and vehicle dynamics. Simulations demonstrate the convergence and adaptability of the proposed strategy in different road scenarios. In addition, our shared control scheme can effectively assist drivers with different characteristics to achieve ideal steering control performance and reduce their driving workload.
A 3D Computational Fluid Dynamics and Acoustics Simulation Approach for Noise Mitigation Prediction in Gerotor Pumps
Authors: Taghizadeh Salar , Ng Kok Chian , Horen Jezrah , Dhar Sujan
Published: April 2024

Positive displacement pumps are key components in automotive and hydraulic fluid systems, often serving as the primary power source and a major source of noise in both on-highway and off-highway vehicles. Specifically, gerotor pumps are widely utilized in vehicle coolant, lubricating, and other fluid systems for both conventional and electric powertrains. This study introduces a novel method for predicting noise in gerotor pumps by combining a Computational Acoustics (CA) approach with a 3D Computational Fluid Dynamics (CFD) approach, both implemented in the Simerics–MP+ code. The CFD simulation includes the detailed transient motion of the rotors (including related mesh motion) and models the intricate cavitation/air release phenomena at varying pump speeds. The acoustic simulation employs a Ffowcs–Williams Hawkings (FW–H) integral formulation to predict sound generation and propagation based on the detailed flow field predictions from the CFD model.

Simulations of two different gerotor pump designs were conducted under a wide range of operating conditions, resulting in the prediction of a full range of sound pressure spectra across various sound frequencies. These simulation results are compared with sound pressure measurements, revealing that the simulation approach can effectively predict the relative sound pressure distribution across the frequency spectrum. Notably, the mitigation of sound pressure at specific regions of the frequency–RPM spectrum was accurately captured. This paper provides a comprehensive insight into the modeling methodology, the experimental measurement methods, and compares the sound pressure spectra obtained from simulations and experiments. This proposed method harnesses the ability to obtain detailed, high–fidelity 3D flow field and cavitation/air release solutions in positive displacement machines and demonstrates excellent potential for predicting noise improvements resulting from pump design changes. Thus, it offers valuable insights for designing quieter pumps.
A Holistic Approach to Mitigating Warpage in Fiber-Reinforced Plastic Injection Molding for Automotive Applications
Authors: Seo Kyeong-Bae , Park Sang Sun , Lee ChoonSoo
Published: April 2024

Fiber-reinforced plastics (FRPs), produced through injection molding, are increasingly preferred over steel in automotive applications due to their lightweight, moldability, and excellent physical properties. However, the expanding use of FRPs presents a critical challenge: deformation stability. The occurrence of warping significantly compromises the initial product quality due to challenges in part mounting and interference with surrounding parts. Consequently, mitigating warpage in FRP-based injection parts is paramount for achieving high-quality parts. In this study, we present a holistic approach to address warpage in injection-molded parts using FRP. We employed a systematic Design of Experiments (DOE) methodology to optimize materials, processes, and equipment, with a focus on reducing warpage, particularly for the exterior part. First, we optimized material using a mixture design in DOE, emphasizing reinforcements favorable for warpage mitigation. After careful consideration of physical properties, deformation stability, and economic feasibility, PP-Mica10+GF5 emerged as the optimal material. Next, we fine-tuned the injection processes for the selected material. We applied the response surface design in DOE, considering key process factors. This approach led to the identification of ideal conditions that minimize warpage. Finally, we addressed equipment optimization by designing a fixing jig, informed by injection molding simulations and real-world part deformations. In conclusion, we validated the optimized materials, processes, and equipment through real exterior part, resulting in an impressive 85% reduction in warpage, meeting stringent product design standards. This holistic approach serves as a versatile design methodology applicable to various FRP injection-molded parts, offering a promising pathway for warpage mitigation in the industry.
Development of Oxygenated Diesel Fuel and Impact on Vehicle Performance
Authors: Chakradhar Maya , Chakrahari Kiran K. , Prakash Shanti , Raj Justin , Arora Ajay , Maheshwari Mukul , Harinarain Ajay
Published: April 2024

World is moving towards cleaner, greener and energy efficient fuels.

The rapid increase in the consumption of petroleum fuel has led to twin problem of air pollution and energy security. India being a developing nation, fuel demand and consumption in various industries, especially in road transport sector has been rising continuously. Fossil fuels are the main source of energy and approximately 85% of domestic need met through import of crude oil. The increasing fuel consumption has created interest for the blending of biofuels in conventional fuel and renewable fuels also. Among biofuels ethanol is one of them and preferable choice for blending in gasoline which is a fuel for spark ignition engines and flex fuel vehicles. As such ethanol/methanol cannot be used in compression-ignition diesel engines without engine modifications due to inherent low cetane number and lubricity of alcohols. Therefore, fuel consisting of certain concentrations of alcohols such as methanol/ethanol in diesel blends is being promoted.

The lower alcohols (methanol/ethanol) are not miscible in diesel due to their polarity differences. An additive package is essential for the solubility and stability of alcohol (methanol/ethanol) in diesel phase or diesel blends. Since diesel fuel pumps operate at much higher pressure (up to 220MPa in high-pressure diesel fuel pumps) than the gasoline pumps, oxygenated diesel blends must impart adequate lubricity to metallic parts of fuel delivery system and engine. Lubricity is the one of the important property of diesel specifications (IS: 1460-2017) and appropriate dosing of additive package is compulsory to maintain the specifications of oxygenated diesel blends / alcohol-diesel blends. To tackle the low cetane number, lubricity issue and stability of alcohol-diesel blends, suitable chemistry and dosage of additive package was optimized. Fuel properties of conventional diesel vis-a-vis oxygenated diesel blends having methanol/ethanol up to 15% (v/v) along with appropriate additive package comprising of lubricity improver (LI), cetane improver (CI) and corrosion inhibitor were studied. In this paper, the detailed critical properties of conventional diesel versus oxygenated diesel blends are discussed.
Particulate filter performance mapping for in-service conformity
Authors: Viswanathan Sandeep , Sadek Ghadi , Reddy Vishal , He Suhao , Alam Rabeka
Published: April 2024

The proposed Euro-7 regulations are expected to build on the significant emissions reductions that have already been achieved using advanced Euro VI compliant after treatment systems (ATS). The introduction of in-service conformity (ISC) requirements during Euro VI paved the way for enabling compliance during real-world driving conditions. The diverse range of applications and resulting operating conditions greatly impact ATS design and the ability of the diesel particulate filter (DPF) to maintain performance under the most challenging boundary conditions including cold starts, partial/complete regenerations, and high passive soot burn operation. The current study attempts to map the particle number (PN) filtration performance of different DPF technologies under a variety of in-use cycles developed based on field-data from heavy duty Class-8 / N3 vehicles. Access to such performance maps can allow original equipment manufacturers (OEMs) to select DPF technologies to suit different applications with a better understanding of underlying limitations. The potential inclusion of secondary emissions from diesel exhaust fluid (DEF) injection adds further uncertainty to ATS design including the likelihood of a secondary filter. Different secondary filter technologies were evaluated for DEF PN filtration performance and suitable candidates were identified for SCR systems with reasonable levels of DEF emissions and / or relaxed regulatory limits (>2E11 #/kWh). These results highlight the various product options available to OEMs to meet upcoming Euro-7 HD regulations with suitable safety margins.
Effect of Residence Time on Morphology and Nanostructure of Soot in Laminar Ethylene and Ammonia-Ethylene Flames
Authors: Qian Weiwei , Shi Xiuyong , Li Song
Published: April 2024

As one of the pollutants that cannot be ignored, soot has a great impact on human health, environment, and energy conversion. In this investigation, the effect of residence time (25ms, 35ms, and 45ms) and ammonia on morphology and nanostructure of soot in laminar ethylene flames has been studied under atmospheric conditions and different flame heights (15 mm and 30 mm). The transmission electron microscopy (TEM) and high-resolution transmission electron microscope (HRTEM) are used to obtain morphology of aggregates and nanostructure of primary particles, respectively. In addition, to analyze the nanostructure of the particles, an analysis program is built based on MATLAB software, which is able to obtain the fringe separation distance, fringe length, and fringe tortuosity parameters of primary particles, and has been verified by the multilayer graphene interlayer distance. It is found that soot is mainly composed of tens of primary particles in the form of tree-like at HAB (height above burner) = 30 mm. But the primary particles are dispersed with the use of ammonia at HAB = 15 mm. Moreover, the mean diameter of primary particles is greatly affected by fuels and it is mainly distributed between 16 nm–36 nm. For ethylene flame, it increases first and then decreases with the increase of residence time. For the ethylene ammonia flame, it keeps rising. In addition, the mean fringe separation distance and fringe tortuosity are not affected by residence time. However, with the increase of residence time, the mean fringe length decreases first and then increases for ethylene flame, while for ethylene ammonia flame, the mean fringe length decreases. Furthermore, with the addition of ammonia, the mean separation distance decreases and the mean fringe length increases slightly.
Evaluating the Effects of an Electrically Assisted Turbocharger on Scavenging Control for an Opposed Piston Two Stroke (OP2S ) Compression Ignition Engine
Authors: Bhatt Ankur , Gandolfo John , Huo Ming , Gainey Brian , Lawler Benjamin
Published: April 2024

Opposed piston two-stroke (OP2S) diesel engines have demonstrated a reduction in engine-out emissions and increased efficiency compared to conventional four-stroke diesel engines. Due to the higher stroke-to-bore ratio and the absence of a cylinder head, the heat transfer loss to the coolant is lower near ‘Top Dead Center.’ The selection and design of the air path is critical to realizing the benefits of the OP2S engine architecture. Like any two-stroke diesel engine, the scavenging process and the composition of the internal residuals are predominantly governed by the pressure differential between the intake and the exhaust ports. Without dedicated pumping strokes, the two-stroke engine architecture requires external devices to breathe. In the unique OP2S engine architecture studied in this work, the external pumping devices present in the air path include an electrically assisted turbocharger (EAT), an electrified EGR pump, and a back-pressure valve (BPv) located downstream of the turbocharger.

In this work, various sweeps were experimentally recorded for these actuators to understand their effects on airflow rate, port pressure, and pressure differential. The objective of these experiments was to identify regions with high scavenging efficiencies while evaluating the effect of electrical power consumption as pumping losses on brake efficiency. The results indicated a higher scavenging efficiency was achievable at low engine speeds as less of the fresh intake charge is short-circuited to the exhaust during the blow down process. Also, with the combination of these actuators, an inherent challenge of decoupling airflow control from intake port pressure became apparent, and thus optimizing scavenging at a given port pressure became difficult. However, the EAT provides the flexibility of changing the air flow rate at a constant load but any increase in the brake thermal efficiency is negated by the electrical energy consumed from pumping more air through the compressor.
Multicast Transmission in DDS Based on the Client-Server Discovery Model
Authors: Li Binqi , Zhu Yuan , Lu Ke , Zhong Xu , Sun Zhipeng
Published: April 2024

The functions of modern intelligent connected vehicles are becoming increasingly complex and diverse, and software plays an important role in these advanced features. In order to decouple the software and the hardware and improve the portability and reusability of code, Service-Oriented Architecture (SOA) has been introduced into the automotive industry. Data Distribution Service (DDS) is a widely used communication middleware which provides APIs for service-oriented Remote Procedure Call (RPC) and Service-Oriented Communications (SOC). By using DDS, application developers can flexibly define the data format according to their needs and transfer them more conveniently by publishing and subscribing to the corresponding topic. However, current open source DDS protocols all use unicast communication during the transmission of user data. When there are multiple data readers subscribing to the same topic, the data writer needs to send a unicast message to each data reader individually. Obviously, this unicast transmission method not only brings queuing delay to the later readers, but also reduces the transmission efficiency of DDS. This paper proposes a multicast transmission method based on the client-server discovery mechanism, where the discovery server allocates a multicast address and a listening port to a specific topic. In this way, the data writer only needs to send one multicast message and then all data readers will receive this data message. To compare the performance of the unicast and the multicast transmission mechanisms, we designed multicast working conditions to test their performance in terms of latency and sending efficiency. Experimental results show that the multicast transmission method can eliminate the extra delay generated by the original unicast method, and can significantly improve the transmission efficiency of DDS.
Inverter Thermal Dimensioning for Electrical Driven Compressor
Authors: Banumurthy Hariharan , Ribot Herve , Leon Renan , Francois Nicolas , Sattouf Mousa , Marouf Ayyoub
Published: April 2024

The inverter of the electrical driven compressor (EDC) is subjected to high thermal loads which are resulting from external temperature exposure and from compressor solicitations from the vehicle thermal loop (refrigerant nature, flow rate, compression rate, initial temperature). An incorrect thermal management of the inverter might lead to a significant decrease of efficiency which degrades the performance, product lifetime (electronics components failure) and even worse, might lead to a hazardous thermal event (HTE).

The need of the automotive market to drastically decrease project development time, requires decreasing design and simulation activities lead time without degrading the design robustness, which is one additional complexity and challenge for the R&D team. Analytical calculations are performed to understand the significant impact of the main physical parameters (refrigerant temperature, material properties, electronics component power dissipation, …) on the initial design definition. This would help to save time to optimize the design before delivering to the numerical methods.

In this paper, the development process of the inverter product, based on systems engineering methodology, is briefly described. The systems engineering approach allows to define the good inverter architecture and design solutions. It ensures the testing of all requirements at different levels (electronics components, inverter, compressor, …). Multi-fidelity simulation approach on multiple levels (individual components level till full system level) is also described. Working on multilevel simulations accelerates the design activities and provides proper design justification to ensure design robustness. Correlation between simulation and test results is also shown in this paper.
Thermal Management Development for a Dedicated Hybrid Engine
Authors: Xu Zheng , Xia QiWei , Peng Chao , wang YanJun
Published: April 2024

The high-efficiency dedicated hybrid engine (DHE) has led to increasingly complex challenges in engine thermal management. On one hand, the high compression ratio of up to 16:1 makes the engine more susceptible to knocking, necessitating meticulous thermal management to mitigate the potential sensitivity to metal temperature. On the other hand, extensive use of external cooled exhaust gas recirculation (EGR) helps reduce knocking and improve thermal efficiency, but it also raises temperature levels and requires additional cooling measures.

For the 1.5L DHE developed by SAIC Motor, a split cooling structure was employed in the engine cooling system design, with the cylinder head water jacket and cylinder block water jacket arranged in parallel and equipped with different coolant outlets. By utilizing a dual thermostat to control flow, this design allows for adjustable flow distribution, providing effective cooling to the cylinder head while reducing cooling to the cylinder block. The block thermostat can close the flow of the block water jacket before the water temperature reaches the opening temperature, enabling quick warming of the cylinder block.

Furthermore, an electric water pump was employed as an ideal solution for the DHE, eliminating the need for a front-end drive system. This helps reduce parasitic losses due to accessories and improve overall efficiency. As the primary driving source for coolant in the entire cooling system, the electronic water pump plays a crucial role in the overall thermal management system. Specialized control strategies and software have been developed to optimize its performance.

This paper presents the development of thermal management, including cooling system design and simulations, as well as test development. It also elaborates on the control strategy development for the electric water pump, which meets the requirements of the engine and vehicle under various environmental and operating conditions.
A Study on Reliability-Based Maximum Service Temperature Estimation of Plastic Automotive Parts
Authors: Youn Jee Young , Chung Min Gyun , Ahn Hyo Sang
Published: April 2024

Recently, the environmental temperature of vehicles is changing due to the electrification of vehicles and improved internal combustion engine system to reduce carbon emissions. However, mechanical properties of plastic materials change very sensitively to environmental temperature changes, and mechanical properties decrease when exposed to high temperatures. Therefore, it is important to estimate lifespan estimation of plastic parts according to temperature changes. In this paper, reliability analysis process to estimate the maximum service temperature of plastic parts was developed using aging data of material properties, environmental condition data of automotive parts, and field driving condition data. Changes in the mechanical properties of plastic materials such as glass fiber reinforced polyamide materials were tested. The environmental exposure temperature of the vehicle and parts was measured, and the general driving pattern of the vehicle was analyzed. Weibull aging model and Arrhenius physics model was applied for lifespan estimation of materials. The damage rate theory was applied to obtain the sum of damage rates in various temperature conditions since automobiles are exposed to various temperature conditions. The damage rate according to the temperature and time exposed to the environment was calculated with lifespan estimation results of materials and environment conditions of plastic parts, then the maximum service temperature that can satisfy the warranty period of the product was predicted. As case studies, the maximum service temperature of the air intake manifold, the bracket part that support the motor in EVs or the transmission in internal combustion engines with glass fiber reinforced polyamide was predicted with reliability-based maximum service temperature estimation method.
High Dimensional Preference Learning: Topological Data Analysis Informed Sampling for Engineering Decision Making
Authors: Mollan Calahan , Morkvenaite-Vilkonciene Inga , Pandey Vijitashwa
Published: April 2024

Engineering design-decisions often involve many attributes which can differ in the levels of their importance to the decision maker (DM), while also exhibiting complex statistical relationships. Learning a decision-making policy which accurately represents the DM’s actions has long been the goal of decision analysts. To circumvent elicitation and modeling issues, this process is often oversimplified in how many factors are considered and how complicated the relationships considered between them are. Without these simplifications, the classical lottery-based preference elicitation is overly expensive, and the responses degrade rapidly in quality as the number of attributes increase. In this paper, we investigate the ability of deep preference machine learning to model high-dimensional decision-making policies utilizing rankings elicited from decision makers. To aid in the training of this machine learner, we propose a topological data analysis (TDA)-based algorithm to select the group of elicitations which would best fill the experimental space. Finally, we apply the proposed method on a vehicle design selection problem involving 19 attributes, discuss the results, and identify avenues for future work.
Enhancing Vehicle Architecture Development: A Robust Approach to Predicting Ride and Handling Performance and Optimization through Reliability Analysis
Authors: Ji-In Jung
Published: April 2024

Global automobile manufacturers are increasingly adopting vehicle architecture development systems in the early stages of product development. This strategic move is aimed at rationalizing their product portfolios based on similar specifications and functions, with the overarching goal of simplifying design complexities and enabling the creation of scalable vehicles. Nevertheless, ensuring consistent performance in this dynamic context poses formidable challenges due to the wide range of design possibilities and potential variations at each development stage. This paper introduces an efficient reliability analysis process designed to identify and mitigate the distribution of Ride and Handling (R&H) performance. We employ a range of reliability analysis techniques, including Latin Hypercube Sampling and the enhanced Dimension Reduction (eDR) method, utilizing various types of models such as surrogate models and multi-body dynamics models. This approach is applied to predict R&H performance and facilitate Reliability-based Design Optimization (RBDO), accounting for design range and accumulated tolerance within suspension geometry, all directed toward achieving target performance. By establishing this efficient reliability analysis process, our study not only advances the understanding of R&H performance but also provides a valuable framework for extending this approach to enhance efficiency in other performance areas during the early stages of vehicle development. This extension holds the potential to elevate development efficiency by fostering performance robustness throughout the entire development process
The Basis of Automotive Engineering Accelerated Testing
Authors: Klyatis Lev
Published: April 2024

This paper reviews the current situation in the development of accelerated testing of automotive engineering, consisting of the four following areas:

1.
Field testing of the natural product.

2.
Additional technology of separate testing in the laboratory on the basis of physical simulation of separate field conditions using corresponding methods and equipment separately and conducting: safety testing, special programs of testing using digital simulation, special testing with changing certain parameters of environment, corrosion testing, etc. Both of the traditional testing developments above can be found in many magazines, journals, conferences, presentations, and proceedings.

3.
Testing on the basis of digital (computer) simulation of product and/or field conditions. This area of testing has been developed in the last dozen years. Many articles and presentations were published during this time.

4.
Accelerated reliability and durability testing for obtaining during service-life of the product’s initial information for successful prediction of product efficiency and its components such as safety, reliability, durability, maintainability, supportability, life-cycle cost, profit, etc. This area is less developed, because it is much more complicated and expensive, with long horizons for return on investment.

Finally, the paper includes the author’s recommendations for improving the current situation.
Lithium-Ion Battery SOC Estimation Method Based on LSSVM-UKF
Authors: Zhu Haotian , Lu Yangtian
Published: April 2024

Since entering the 21st century, the world has faced extremely serious environmental pollution and energy crises. In this context, new energy vehicles have been vigorously developed. Lithium-ion batteries have gradually become one of the most important energy sources for electric vehicles due to their excellent performance. State of charge (SOC) is one of the important indicators of the battery. Accurate estimation of SOC is of great significance to establishing a safe and accurate Battery management system (BMS).

Among related methods for SOC estimation, observation-based methods have been widely used. However, this type of method has the disadvantages of being susceptible to disturbance and requiring high accuracy of the battery model. The traditional equivalent circuit model cannot meet the needs. This paper proposes a battery SOC estimation method based on LSSVM-UKF through research on lithium-ion battery modeling and SOC estimation methods. First, the least squares support vector machine (LSSVM) is used to model the battery. During the training process of LSSVM, Northern Goshawk optimization (NGO) is used for parameter optimization to improve the fitting performance of the model. In addition, a time window mechanism is introduced to allow the current sampling point data and historical data to be integrated during training to more accurately capture the timing characteristics of the battery system. After building the battery model, the unscented Kalman filter (UKF) is used for battery SOC estimation.

In the verification experiment, this paper used public data sets to verify the battery model accuracy and SOC estimation performance under different ambient temperatures. The results show that in most cases, the error of the battery model does not exceed 0.05V, with only slight fluctuations under medium and high temperatures. UKF has a certain error in the initial stage, but it can adjust quickly. The error does not exceed 0.07 under low temperatures and the error does not exceed 0.03 under medium and high temperatures, showing high accuracy and robustness.