Electric Vehicle Powertrain System Research Articles

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.

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.

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.

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

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.

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.

Testing and implementation of dual way DC-DC converter for electric vehicle power train system

Testing and implementation of dual way DC-DC converter for electric vehicle power train system

Route Towards Road Freight Electrification in India: Examining Battery Electric Truck Powertrain and Energy Consumption

Medium-duty/heavy-duty trucks (MD/HDTs) are yet to be included in India's electric mobility plans. With the improvement of electric vehicle (EV) technologies, there is a growing interest in battery-electric trucks (BETs) from original equipment manufacturers (OEMs). The time is opportune to consider electrification as a future direction for road freight in India. Accordingly, this article presents the results of an energy consumption simulation study of a BET under Indian conditions. This study specifically considered an MDBET over a domestic drive cycle. These energy consumption figures can facilitate future studies that analyze the technical and practical feasibility of BETs in the country. In addition, the article provides the requisite groundwork for BET modeling for a simulation study by reviewing available EV powertrain systems and components. Appropriate powertrain considerations are thereby obtained for a typical medium-duty/heavy-duty battery-electric truck (MD/HDBET) in the Indian context.

Modeling and analysis of dynamic characteristics of rubber isolators for electric vehicles under high-frequency excitation

The rubber isolator is a key component connecting the vehicle body and the powertrain, which plays a significant role in reducing the vibration transmission from the engine to the vehicle body. With the development of electric vehicles, the excitation frequency generated by the powertrain can exceed 2 kHz. The conventional dynamic models are usually used to simulate the low-frequency dynamic characteristics of rubber isolators, in the range of 0–200 Hz, which is the main excitation frequency range of the traditional internal combustion engine vehicle. However, they cannot simulate the high-frequency dynamic characteristics accurately since the inertial force caused by the mass of rubber isolators increases greatly under high frequencies. And the high-frequency dynamic characteristics of rubber isolators is of great significance for isolator fatigue life prediction, powertrain system vibration isolation design and noise control caused by the high-frequency resonance of the isolator. In this paper, a general model with mass elements is proposed to describe the effect of the inertial force on high-frequency dynamic stiffness. Based on the proposed model and considering the different expressions of the viscoelastic properties of rubber isolators, three improved dynamic models of rubber isolators are established, and used to analyze the high-frequency dynamic characteristics of rubber isolators. It has been demonstrated that the inertial force plays a non-negligible role in the dynamic characteristics of rubber isolators under high-frequency excitation. The proposed model can be used to analyze the effect of the inertial force on the dynamic characteristics at high frequencies accurately. The high-frequency dynamic characteristic modeling method of rubber isolators presented in this paper is helpful to the vibration and noise analysis of electric vehicle powertrain systems under high-frequency excitation.

Electric Vehicle Mechanical Transmission System Based on Fractional Differential Equations

Abstract This paper introduces a method for dynamic loading of human-vehicle powertrains during dangerous driving. At the same time, this paper establishes a performance evaluation index of the human-vehicle (electric vehicle) powertrain system based on the second derivative functional. We have analyzed and established the calculation formula of the excitation force of the electric vehicle drive train in unstable driving conditions. We use the numerical solution method to perform the dynamic model simulation calculation on MATLAB. The study found that the high-frequency excitation force increases the amplitude of the acceleration power spectrum of the electric vehicle system. At the same time, the research results prove that the state-space model of the electric vehicle vibration system and the selected parameter values are effective.

Investigation on Current Ripple and Electromagnetic Interference in High Voltage Powertrain Systems for Electric Vehicles by Using Crosslinked Polyolefin Insulation Shielded Cable

At this moment, the powertrain system of Electric Vehicles (EVs) tends to use high voltages and high currents when the EVs operate at High Power (HP) mode. The Electromagnetic Interference (EMI) is caused by Electromagnetic Field (EF), high voltage, and current ripple. EMI affects EVs, whereas the Shielding Effectiveness (SE), and the proportional inverse of the transfer impedance prevent the effect of EMI. This research aims to investigate the current ripple the EMI in high voltage powertrain systems for EVs by using the developed crosslinked polyolefin insulation shielded cable, 50 mm2 single-core HP XLPO shielded cable with 0.15 mm annealed tinned-copper wire braid material. The experiment consists of three parts. The first one investigates the tendency of SE and current ripple. The second part shows the analysis of the effect of HP mode to the cable. The third part is an additional study that compares and analyzes the transfer impedance. The results indicate that the cable operates properly in the frequency above 200 Hz, transfer impedance decreasing between 11.5% to 15.25%, induces the SE and reduces the current ripple in the higher frequency range. The results obtained from this research represent a preliminary investigation guideline in decreasing the effect of EMI in EVs by using 50mm2 single-core HP XLPO shielded cable with 0.15 mm annealed tinned-copper wire braid material in a high-power range.

Co-Optimization Scheme for the Powertrain and Exhaust Emission Control System of Hybrid Electric Vehicles Using Future Speed Prediction

Hybrid electric vehicles (HEVs) have been an effective solution for improved vehicle fuel efficiency and reduced emission pollution. However, the optimization design for HEVs is complicated due to the presence of nonlinear dynamics and complicated integration of the HEV systems. Moreover, there is a trade-off between fuel optimization and emission reduction. In this paper, a co-optimization scheme is proposed to optimize fuel efficiency for HEVs. The proposed optimization scheme uses obtainable future speed prediction as the basis to optimally tune control parameters for the existing powertrain control system. Moreover, the ramp-up time of the catalyst temperature to reach its light-off level in the exhaust emission system is also considered as an additional optimization constraint to reduce emission. At first, the Toyota Prius Hybrid Simulink model which is an integrated model for a powertrain and exhaust emission system is validated using real data from a number of real driving cycle scenarios. Then, to simplify the formulation of the proposed algorithm, the model employed for the optimization for both powertrain and exhaust emission systems is represented by a set of equivalent neural network (NN) models, which are learned using the data generated from the well-validated Toyota Prius Hybrid Simulink model. Using the NN model, a co-optimization algorithm is established that provides an optimal tuning of some fuel-sensitive powertrain control parameters using future speed prediction, leading to a novel co-optimization algorithm, achieving on average a further 9.22% fuel savings for the Toyota Prius Hybrid Simulink model.

A Bidirectional Versatile Buck-Boost Converter Driver for Electric Vehicle Applications.

This work presents a novel dc-dc bidirectional buck–boost converter between a battery pack and the inverter to regulate the dc-bus in an electric vehicle (EV) powertrain. The converter is based on the versatile buck–boost converter, which has shown an excellent performance in different fuel cell systems operating in low-voltage and hard-switching applications. Therefore, extending this converter to higher voltage applications such as the EV is a challenging task reported in this work. A high-efficiency step-up/step-down versatile converter can improve the EV powertrain efficiency for an extended range of electric motor (EM) speeds, comprising urban and highway driving cycles while allowing the operation under motoring and regeneration (regenerative brake) conditions. DC-bus voltage regulation is implemented using a digital two-loop control strategy. The inner feedback loop is based on the discrete-time sliding-mode current control (DSMCC) strategy, and for the outer feedback loop, a proportional-integral (PI) control is employed. Both digital control loops and the necessary transition mode strategy are implemented using a digital signal controller TMS320F28377S. The theoretical analysis has been validated on a 400 V kW prototype and tested through simulation and an EV powertrain system testing.

Enhancing the efficiency of electric vehicle’s motor using electro-mechanical continuously variable transmission

Over the last decades, significant progress has been made on the technologies of battery electric vehicle (BEV) powertrain system. As a result, the driving mileage of the latest EVs has been improved tremendously, making the ownership of BEV more viable now. Nevertheless, even with the latest progress, the driving mileage of a BEV is still generally lower as compared to the vehicle with an advanced internal combustion engine. Thus, this paper investigates the potential of increasing the mileage of a BEV further by using electro-mechanical continuously variable transmission (EMCVT) in its powertrain system. The purpose of the EMCVT is to allow the electric motor used in the BEV powertrain system to operate in its most efficient condition for a wide range of vehicle’s speeds. This condition is defined using the efficiency mapping of a typical electric motor applied in the existing BEVs. Based on this mapping, the motor’s efficiency when used with EMCVT is compared with the efficiency of the same motor when used with a single speed transmission for various vehicle speeds. In this investigation, the efficiency of the EM CVT is considered at 75% to 95%, and the BEV with EMCVT is considered to be 80 kg heavier than the BEV using a single speed transmission. The comparison between the BEV with and without EMCVT shows that the application of EMCVT allows the motor to operate in its most efficient condition for a wider range of the vehicle’s velocity. However, the improved motor’s efficiency is compromised by the losses in the EMCVT, making it challenging to achieve lower power consumption during driving. Therefore, to achieve meaningful improvement in terms of power consumption, the efficiency of the EMCVT has to be higher than 85%.

Analysis of Vibration and Noise for the Powertrain System of Electric Vehicles under Speed-Varying Operating Conditions

Whine noise from the electric powertrain system of electric vehicles, including electromagnetic noise and gear-meshing noise, significantly affects vehicle comfort and has been getting growing concern. In order to identify and avoid whine problems as early as possible in the powertrain development process, this paper presents a vibration and noise simulation methodology for the electric powertrain system of vehicles under speed-varying operating conditions. The electromagnetic forces on the stator teeth of the motor and the bearing forces on the gearbox for several constant-speed operating conditions are obtained first by electromagnetic field simulation and multi-body dynamic simulation, respectively. Order forces for the speed-varying operating condition are generated by interpolation between the obtained forces, before they are applied on the mechanical model whose natural modes have been calibrated in advance by tested modes. The whine noise radiated from the powertrain is then obtained based on acoustic boundary element analysis. The simulated bearing forces indicate that the overlooking of the motor torque ripple does not result in significant loss in simulation accuracy of electromagnetic noise. The simulation results and tested data show good consistency, with the relative frequency deviation of local peaks being less than 8% and the error of the average sound pressure level (SPL) being mostly below 10 dB (A).

A Decentralized Energy Management Strategy for a Fuel Cell–Battery Hybrid Electric Vehicle Based on Composite Control

Traditionally, the energy management objectives of a fuel cell-battery hybrid electric vehicle (FCBHEV) powertrain system is achieved by using the centralized control strategy, which suffers from poor flexibility, scalability, and reliability. What is worse, the system stability can hardly be guaranteed because of the serious interactions between the fuel cell (FC) as well as the battery converters and motor drive loads. In this article, a decentralized energy management strategy (EMS) based on a composite control scheme that combines mixed droop control and disturbance-observer-based control is proposed to achieve the dynamic load power allocation, extend the service life, improve the energy efficiency, enhance the robustness (i.e., realize the disturbance and uncertainty rejection), and guarantee the global stability of the FCBHEV powertrain system in a decentralized way simultaneously. First, the architecture of an FCBHEV powertrain system is described in detail. Then, analyses on the design and operating principle of the proposed EMS are deeply studied. Finally, a hardware-in-the-loop (HIL) real-time simulation system of a 50 kW FCBHEV powertrain system is established using the Typhoon HIL 602 device. The HIL simulation results verified the correctness of the theoretical analysis and effectiveness of the proposed EMS.

Influence and Optimization of Packet Loss on the Internet-Based Geographically Distributed Test Platform for Fuel Cell Electric Vehicle Powertrain Systems

In view of recent developments in fuel cell electric vehicle powertrain systems, Internet-based geographically distributed test platforms for fuel cell electric vehicle powertrain systems become a development and validation trend. Due to the involvement of remote connection and the Internet, simulation with connected models can suffer great uncertainty because of packet loss. Such a test platform, including packet loss characteristics, was built using MATLAB/Simulink for use in this paper. The simulation analysis results show that packet loss affects the stability of the whole test system. The impact on vehicle speed is mainly concentrated in the later stage of simulation. Aiming at reducing the effect of packet loss caused by Internet, a robust model predictive compensator was designed. Under this compensator, the stability of the system is greatly improved compared to the system without a compensator.