Vehicle Powertrain System Research Articles

Research on Failure Characteristics of Electric Logistics Vehicle Powertrain Gearbox Based on Current Signal

As a core component of the powertrain system of Electric Logistics Vehicles (ELVs), the gearbox is crucial for ensuring the reliability and stability of ELV operations. Traditional fault diagnosis methods for gearboxes primarily rely on the analysis of vibration signals during operation. This paper presents research on diagnosing gear tooth wear faults in ELV powertrains using motor current signals. Firstly, an experimental test platform was constructed based on the structural principle of the powertrain of ELV models. Subsequently, a pure electric light truck powertrain gearbox with tooth wear was tested. Time–frequency domain analysis, amplitude analysis, ANOVA analysis, kurtosis analysis, and zero−crossing points analysis were used to analyze the U−phase current of the motor connected to the gearbox to study the characteristics of the phase current of the drive motor after tooth wear. The results indicate that while the time–frequency domain characteristics of the U−phase currents are not significantly altered by tooth wear faults, the amplitude, variance, and kurtosis of the current increase with the severity of the wear. Conversely, the number of zero−crossing points decreases. These findings provide valuable insights into new methodologies for diagnosing faults in ELV powertrain systems, potentially enhancing the efficiency and effectiveness of troubleshooting processes.

Nonlinear modeling and torsional vibration analysis of heavy-duty vehicle powertrain system during acceleration

Nonlinear modeling and torsional vibration analysis of heavy-duty vehicle powertrain system during acceleration

Development and Performance Analysis of Commercial Vehicle Axle Shaft

Axle shafts, which are an important part of the vehicle's powertrain system, transfer the torque to the wheels and enable the vehicle to move. In this respect, the design of the axle shaft to be used in a new vehicle is of great importance for vehicle manufacturers. When a cylindrical shaft is torsionally loaded, the shear stress is highest at the surface of component and zero at the center. Therefore, these axle shafts are exposed to an induction hardening process that enables only this superficial case to have its properties changed, remaining the core zone with its material original characteristics. Current study presents the results of a project aimed at developing and evaluating the fatigue life of axle shaft that belongs to a commercial vehicle. Developments were made on the existing axle and the results were examined using experimental tests and finite element analysis method. In line with the improvements made, the developed axle shaft has 331.7% more fatigue life than the existing axle, while the cost is 24% lower. According to these results, more attention must be paid to material selection, induction hardening process, stress concentration and surface condition of axle shaft in the design. This study involves many disciplines such as design, manufacturing, analysis, testing, etc. It is very important to ensure communication between all these disciplines in the production of the product. The output obtained from one discipline becomes the input of another discipline. In the cumulative sum of all these inputs, the optimum level of parts is obtained. For this reason, this study, which processes all these disciplines together, is very valuable.

Comparative Simulation Analysis of Electric Vehicle Powertrains with Different Configurations Using AVL Cruise and MATLAB Simulink

Electric vehicles are now recognized as a crucial answer in the worldwide effort to achieve sustainable and environment-friendly transportation. As the automotive industry moves towards using electric power, it is crucial to assess and improve the powertrain configurations in electric vehicles. This study aims to meet this need by conducting an in-depth comparative analysis of single, double, and quad electric vehicle powertrain systems. The performance of these configurations is rigorously simulated by using two widely used platforms: AVL Cruise and MATLAB Simulink. This study mainly covers the analysis of energy efficiency, which is a critical factor in determining the environmental impacts and feasibility of electric vehicles. In order to conduct a thorough comparison, the energy consumption per kilometer is evaluated as a crucial performance measure. Our research primarily focuses on model validation, namely by comparing it with manufacturer data to determine the accuracy and reliability of the simulation results. The findings reveal a compelling narrative in the pursuit of sustainable transportation. The use of a dual motor setup stands out as a prominent example of energy efficiency, demonstrating remarkable outcomes in both simulation platforms. Significantly, these findings closely correspond with the manufacturer's data for the Volvo XC40, confirming the appropriateness and dependability of our simulation models. Furthermore, the quad motor configuration shows significant energy efficiency, providing helpful insight regarding its applicability and performance. The broader implications of this research go beyond powertrain configurations, including the trustworthiness of simulation models in the automotive industry. These findings improve the continuous advancement of electric vehicle design and development, indicating a more environment-friendly and energy-efficient future for the automotive industry. This study offers invaluable insights and benchmarks for the transition to environment-friendly transportation solutions, as the world advances towards sustainable mobility.

Application of Digital Twin in Electric Vehicle Powertrain: A Review

Digital Twin (DT) is widely regarded as a highly promising technology with the potential to revolutionize various industries, making it a key trend in the Industry 4.0 era. In a cost-effective and risk-free setting, digital twins facilitate the interaction and merging of the physical and informational realms. The application of digital twins spans across different sectors, including aerospace, healthcare, smart manufacturing, and smart cities. As electric vehicles have experienced rapid growth, there is a growing demand for the development of innovative technologies. One potential area for digital twins application is within the automotive sector. The powertrain system of electric vehicles (EVs) consists of three parts, power source, power electronic system, and electric motor, which are considered as the core components of electric vehicles. The focus of this paper is to conduct a methodical review regarding the use of digital twins in the powertrain of electric vehicles (EVs). While reviewing the development of digital twin technology, its main application scenarios and its use in electric vehicle powertrains are analysed. Finally, the digital twins currently encounter several challenges that need to be addressed, and so the future development of their application to electric vehicles are summarized.

Modeling and Load Emulation Experimental Verification of a Vehicle Powertrain System Test Bench Based on Rigid-Flexible Coupling Transmission Shaft

Modeling and Load Emulation Experimental Verification of a Vehicle Powertrain System Test Bench Based on Rigid-Flexible Coupling Transmission Shaft

Modeling and Subjective Evaluation Method of Driveability for Fuel Cell Vehicles

Aiming at the demand for subjective evaluation of driveability for fuel cell vehicles, the modeling and evaluation method of driveability for fuel cell vehicles were studied in this paper. Firstly, a real-time model of the fuel cell vehicle powertrain system was established, which included the fuel cell model, power battery model, DC/DC converter model and drive motor model. Secondly, it was integrated with the vehicle dynamics model to form a virtual prototype of a fuel cell vehicle. And a virtual subjective evaluation platform for fuel cell vehicles was built by combining the virtual prototype and high-fidelity driving simulator. Thirdly, a subjective evaluation method of driveability for fuel cell vehicles was proposed, which included the starting performance, acceleration performance, uniform speed performance and tip-in/tip-out performance. Finally, the paper used the platform and method mentioned above to conduct subjective evaluations of the fuel cell vehicles.

KPI-related monitoring approach for powertrain system in hybrid electric vehicles

This paper introduces a novel monitoring method related to key-performance-indicators (KPIs), specifically tailored for the hybrid electric vehicle (HEV) powertrain system. The proposed method establishes a new KPI that better reflects the performance of the HEV powertrain system. Through the application of partial least squares and contribution plot method, it excels in minimizing data scale and precisely monitoring HEV powertrain faults. Diverging from current methodologies, this method demands minimal prior knowledge and solely relies on previously observed HEV data. The simulation results demonstrate the method's capability to detect engine and motor overheating faults while accurately diagnosing their root causes. In summary, this innovative method marks a significant departure from existing approaches, providing a robust and powerful tool for state monitoring in the HEV powertrain system.

Support vector machine based fault detection in inverter‐fed electric vehicle

AbstractInverters play a prominent role in the power train system of electric vehicles (EVs). Devices in EV connected power system are threatened by faults due to the continuous working and varying speed range of motors in EVs. Hence, in the EV connected application, the detection of fault is essential since it secures the system from severe damage and dangerous operating conditions. This paper deals with fault detection in inverter‐fed EV using a dual‐tree complex wavelet transform (DTCWT) based squeeze net (SN) and optimized support vector machine (SVM). Due to the simple structure and high power density, most EV models on the market are equipped with induction motors. In the proposed work, the voltage, current, and speed signals are measured at different faulty conditions, and then the features are extracted through the DTCWT‐based SN. Extracted data are processed and classified through the sucker‐vulture optimization algorithm (SVOA) based SVM. In the proposed SVOA, the exploration phase of remora optimization algorithm is used for the exploitation phase of African vulture optimization algorithm (AVOA). Thus, the convergence speed of AVOA is improved. The proposed method is implemented in MATLAB/SIMULINK, and the results are used for different scenarios. The accuracy and F1‐score for the proposed methodology are attained as 99.92441% and 99.92441%. From the obtained results, it is clear that the proposed DTCWT‐based SN effectively detects the faults in the inverter.

Investigation on the wet compression performance of a co-rotating scroll hydrogen recirculation pump for fuel cell engine systems

The scroll-type hydrogen recirculation pump is critical for fuel cell vehicle powertrain systems, yet its performance under multiphase conditions remains poorly understood. This study proposes a co-rotating scroll hydrogen pump with array scrolls and investigates its aerodynamic performance, including volumetric efficiency, isentropic efficiency, and power consumption, under varying inlet humidity through 3D transient numerical simulations. Additionally, the effects of operational and geometric parameters (rotational speed, radial clearance, and axial clearance) on the wet compression performance of the pump at the maximum inlet humidity are carried out. Results show that inlet humidity primarily affects the compression and discharge processes of the pump. Increasing inlet humidity suppresses tangential leakage, improving volumetric efficiency, while reducing isentropic efficiency. With inlet humidity increasing from 0% to 100%, the volumetric and isentropic efficiencies change by + 1.84% and −2.3%, respectively, with a power consumption increase of approximately 8.9 W. Higher rotational speeds significantly decrease the isentropic efficiency, while axial clearance has a more pronounced impact on both efficiencies compared to radial clearance. Specifically, increasing rotational speed from 5000 r/min to 15,000 r/min enhances volumetric efficiency by 9.27% and reduces isentropic efficiency by 6.72%. Similarly, increasing radial clearance from 20 μm to 40 μm reduces volumetric efficiency by 5.51% and isentropic efficiency by 0.87%. Raising axial clearance from 20 μm to 40 μm results in a 17.86% drop in volumetric efficiency and 10.7% in isentropic efficiency. These findings offer design insights for high-efficiency co-rotating scroll hydrogen pumps.

Design of the electric vehicle powertrain systems based on μ-analysis

Aiming at the oscillation in the electric vehicle powertrain systems, a control strategy based on the structural singular value [Formula: see text] is proposed. To solve the problem of robustness under parameter uncertainty, the traditional [Formula: see text]-synthesis needs to obtain all-pass characteristics through the weight function in the nominal system, which reduces the perturbation suppression ability of the system. Unlike the previous use of [Formula: see text]-analysis as a system performance criterion, this paper starts from the essence of parameter uncertainty problems and designs controllers based on the relationship between parameter uncertainty and nominal systems, using structural singular value [Formula: see text] as a performance constraint. The result shows that the [Formula: see text]-analysis not only takes into account the robustness and disturbance rejection ability but also reduces the controller order. In addition, the oscillation suppression effect in the presence of transmission backlash is verified, and the [Formula: see text]-analysis can suppress the oscillation better than the [Formula: see text]-synthesis.

Automation program for optimum design of electric vehicle powertrain systems based on artificial neural network

Many studies have been conducted on various powertrain systems, such as multi-motor, multi-speed, or both, to enhance the energy efficiency and dynamic performance of electric vehicles (EVs). This study developed an automated design program to obtain the optimal design of EVs for various powertrain systems. The program consists of an EV simulation and artificial neural network (ANN) modeling and optimization tools. The EV simulation tool employs an integrated EV model that can analyze the efficiency and performance of various powertrain systems in a single environment. The ANN modeling and optimization tool first constructs an ANN model, and then performs optimization using the ANN model to address excessive computational efforts arising from the multi-objective genetic algorithm. This study verified the developed program by conducting analysis and optimization of five powertrain systems with the same EV specifications. A multi-objective optimization problem was formulated by considering the design variables as the torque distribution between the motors and gear shifting patterns and ratios of the transmission, and the objectives as the energy consumption and acceleration time. A comparison of the optimization results among the five powertrain systems quantitatively showed the positive effects of the multi-motor and multi-speed powertrain systems. Furthermore, the ANN-based multi-objective optimization process allowed for the efficient determination of the optimum design solutions for the proposed EV powertrain systems. Consequently, these results demonstrated the effectiveness of the automation program in rapid decision-making on EV powertrain system configurations, satisfying each designer’s requirements.

Influence of Yttria-Stabilized Zirconium Oxide Thermal Swing Coating on the Flame-Wall Interaction in Spark Ignition Engines

Future vehicle powertrain systems with internal combustion engines must achieve higher efficiencies and further reduced pollutant emissions. This will require the application of new advanced technologies. Against this background, this paper presents a holistic approach to reduce temporally the wall heat losses, and hydrocarbon and carbon monoxide emissions with thermal coatings on the combustion chamber walls. For this purpose, an yttria-stabilized zirconia (YSZ) coating is applied and evaluated by different methods. The thin layer in combination with the low thermal effusivity of the material allows the wall temperature to follow the gas temperature and perform a so-called thermal swing. The interaction between an uncoated and a YSZ-coated wall with the flame front as well as partially burned gas was investigated. First, in terms of the coating’s potential to reduce the flame quenching distance using an optical method in a constant volume combustion chamber. Second, regarding its influence on the near-wall gas composition, which was analyzed with in-situ diffuse reflectance infrared Fourier transform spectroscopy measurements and a fast gas sampling technique on a single-cylinder engine. From this, it could be derived that the quenching distance can be reduced by 10% at ambient conditions and by 5% at an elevated temperature of 200 °C by using the coating. These findings also support the results that have been obtained by the near-wall gas composition measurements, where a reduced total hydrocarbon emission was found with the applied coating.

Technology Trend Analysis of Japanese Green Vehicle Powertrains Technology Using Patent Citation Data

As automobiles are major contributors to greenhouse gas emissions, the technological shift towards vehicle powertrain systems is an attempt to lower problems such as emissions of carbon dioxide and nitrogen oxides. Patent data are the most reliable measure of business performance for applied research and development activities when investigating knowledge domains or technology evolution. This is the first study on Japanese patent citation data of the green vehicle powertrains technology industry, using the social network analysis method, which emphasizes centrality estimates and community detection. This study not only elucidates the knowledge by visualizing flow patterns but also provides a precious and congregative method for verifying important patents under the International Patent Classification system and grasping the trend of the new technology industry. This study detects leading companies, not only in terms of the number of patents but also the importance of the patents. The empirical result shows that the International Patent Classification (IPC) class that starts with “B60K”, which includes hybrid electric vehicle (HEV) and battery electric vehicle (BEV), is more likely to be the technology trend in the green vehicle powertrains industry.

Diagnosis of ITSC fault in the electrical vehicle powertrain system through signal processing analysis

1. Cheng M, Sun L, Buja G, Song L. Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles. Energies. 2015; 8(9): 9541-9564. https://doi.org/10.3390/en8099.... CrossRef Google Scholar

Development of Internet-Based Distributed Test Platform for Fuel Cell Electric Vehicle Powertrain System With Observer

As a new form of test validation, fuel cell and Internet-based distributed test platform has gained increasing attention during the period of dual carbon strategy in China. The reliability of the test platform is an important research direction for the distributed test platform. Under the condition of a large international delay during vehicle powertrain system validation and test, how to predict and optimize the system and how to evaluate the optimization effect becomes a research hotspot. In this paper, on the Internet-based distributed test platform for the fuel cell electric vehicle powertrain system, theoretical and simulation analysis of data transmission and dynamic and economic performance is carried out using observer with large time delay. The analysis found that the observer had an impact on vehicle velocity, fuel cell output power, battery output power and electric motor output torque over the entire test system. In addition, the observer can improve system transparency, which measures the subjective feelings of remote distributed system operators, in the above four indicators and almost has no impact on hydrogen consumption. The results of this study provide a powerful theoretical basis for the optimal design of Internet-based distributed test platforms.

Development and application of magnesium alloy parts for automotive OEMs: A review

China is currently vigorously implementing the “energy conservation and emission reduction” and “dual carbon” strategies. As the most resource-advantaged light metal material in China, Magnesium (Mg) alloy is progressively expanding its application in automobile, rail transportation, aerospace, medical, and electronic products. Chongqing University, Shanghai Jiaotong University, and Australian National University have conducted extensive research on the preparation, properties, and processes of Mg alloys. In the past 20 years, the proportion of Mg alloy in the automotive industry has gradually expanded, whereas currently the design and development of Mg alloy parts for automobiles has rarely been reported. Thus, the application models and typical parts cases of Mg alloy are summarized mainly from the four systems of the whole vehicle (body system, chassis system, powertrain system, interior, and exterior system). Subsequently, two actual original equipment manufacturers (OEM) cases are used to introduce the development logic of reliable die-cast Mg alloy, including forward design, formability analysis, process design analysis, structural redesign, manufacturing, and testing, aiming to share the methods, processes, and focus of attention of automotive OEMs for developing Mg alloy parts to enhance the confidence and motivation of applying Mg alloy in automotive field. Eventually, the multiple challenges faced by Mg alloy materials are sorted out and how to face these challenges are discussed. National policies and regulations, environmental protection and energy saving, and consumer demand will continue to promote the application of Mg.

Design and Analysis of Energy Transition in Hybrid Electric Vehicle Power Train Systems

Design and Analysis of Energy Transition in Hybrid Electric Vehicle Power Train Systems

Comparative Analysis of Single, Double and Quad Electric Vehicle Powertrain Systems

Electric vehicles offer a promising solution to solving environmental problems related to air pollution. The typical powertrain design of an electric vehicle includes a relatively high-speed-low-torque electric motor integrated with some mechanical system to transmit the output mechanical energy to the wheels, such as the gearbox, transmission and differential. Different drivetrain configurations with single, double and quad electric motors can be used in electric vehicles. In this study, it is aimed to compare the effects of different powertrain configurations on the acceleration performance, range and energy consumption of the electric vehicle. Single, dual and quad motor electric vehicle powertrain systems were simulated with MATLAB Simulink according to the New European Driving Cycle (NEDC). The Volvo XC40 Recharge electric car was used as the reference vehicle with the same vehicle characteristics, battery type/capacity and the same total power output by changing only the electric motor powertrain configurations. It has been determined that quadruple electric motor powertrain configuration has lower energy consumption, longer range and better acceleration performance than the single and double electric motor powertrain configurations.

Modeling and analysis of high-frequency dynamic characteristics of double isolation rubber mounts

Rubber mounts are the vital component to reduce the vibration translated from the powertrain to the vehicle body. The dynamic stiffness of the conventional rubber mount increase with the increase of the excitation frequency, and form a peak under high-frequency excitation in the battery electric vehicle (BEV). So the double isolation rubber mount has gradually been used in the BEV powertrain to improve the vibration isolation performance in the high-frequency range. Compared with conventional rubber mounts, the double isolation rubber mount has smaller dynamic stiffness in the high-frequency range. However, the traditional simulation model of the dynamic characteristics cannot consider the influence of the metal bracket of the double isolation rubber mount on the dynamic characteristics. Therefore, it is necessary to carry out the modeling and analysis of the dynamic characteristics simulation model of the double isolation rubber mount. In this paper, a general dynamic model of double isolation rubber mounts is proposed to describe the high-frequency dynamic characteristics. In this general dynamic model, the complex stiffness element representing the viscoelasticity of rubber is expressed using the fractional derivative model and the Maxwell model, respectively, and two high-frequency dynamic models are established. Two model parameter identification methods are proposed for high-frequency dynamic models of double isolation rubber mounts, and the identification results are compared and analyzed. Then, two high-frequency dynamic models are used to simulate the high-frequency dynamic characteristics of double isolation rubber mounts. The simulation results show that both high-frequency dynamic models can calculate the high-frequency dynamic characteristics of double isolation rubber mounts. Among them, the dynamic model based on fractional derivative elements has relatively high accuracy, and the dynamic model based on Maxwell elements has relatively high stability. The high-frequency dynamic characteristic modeling method of double isolation rubber mounts presented in this paper is helpful to the vibration and noise analysis of electric vehicle powertrain systems under high-frequency excitation.