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This paper describes a methodology to estimate longitudinal velocity of a 4-wheel-drive electric vehicle, in which wheel driven torque can be independently controlled by electric motor. Without non-driven wheels it would be difficult to estimate the vehicle longitudinal velocity precisely, especially when all of four wheels have large slip ratio. Therefore, an estimation methodology based on fuzzy logic is put forward, which uses four wheel speed and longitudinal acceleration as input signals. However, this method works not very well when two or more wheels have large slip ratio. In order to improve estimation effect, a state variable filter is designed to calculate wheel acceleration signals, which are used as additional signals to the fuzzy logic observer. Furthermore, the possibility of using four wheel driving torque signals to improve the estimation precision is also discussed.

The range-extended electric transit bus (REEbus) equipped with the auxiliary power unit (APU) using high efficient diesel engine as power source can reduce the cost of power battery and is an ideal transitional powertrain architecture to the pure electric drive. Based on chassis tests of a 12m long REEbus, fuel consumption and emission characteristics during Charge-Sustaining (CS) stage effected by temperature of the REEbus are researched. The APU of REEbus starts to work around just one point with best efficiency and lower emission when the state of charge (SOC) is too low and stop when the SOC is high, which aims to lower fuel consumption. As a result, even during CS stage, the fuel consumption of REEbus is only 22.84 L/100km. Also almost all emissions decrease dramatically and the NOx emission is only 0.68g/km, but the ultrafine-particle number increases owing to better combustion.

Based on the four-wheel-drive electric vehicle (4WD EV), a variable structure control (VSC) strategy is designed in this paper for the anti-lock braking control. With nonpeak friction coefficient as target, sign judgment method of switch function in this VSC strategy is improved and a new control algorithm is proposed. The improved VSC strategy is made robust to the parameters of the algorithm and verified by the computer simulation as well as the hard-in-loop test. The results show that the slip rate can be controlled to a point in the stable area near the optimal slip ratio and the control strategy can effectively realize the anti-lock braking control.

As the key assembly of new energy vehicles, the noise and vibration, and harshness (NVH) performance of integrated electric drive system directly affects the driving quality of new energy vehicles. In this paper, the vibration noise characteristic test of 3in1 electric drive system is carried out in the semi-muffler chamber. In order to compare and analyze the difference between 2in1 and 3in1 electric drive system NVH performance, the power electronics unit (PEU) in the 3in1 system was removed and placed on the ground away from the platform, and vibration noise test was carried out. In order to analyze the difference of NVH performance between 2in1 status and 3in1 status, the PEU in the 3in1 system was removed and placed on the ground far away from the bench, and the NVH test was carried out. The microphone signal at 1m position and the vibration acceleration signal of the key structural surface of the system are measured experimentally.

Fuel cells directly convert the energy stored in hydrogen into electrical energy through an electrochemical reaction, and the only reaction product is water, which can improve the energy efficiency and reduce the pollution caused by fossil fuels. The fuel cell hybrid power system used in vehicles usually consists of a fuel cell stack and a power battery module, and the DC/DC converter is the key component to connect them together. The current ripples caused by the system have been confirmed to have detrimental effects on the fuel cell’s reliability and lifespan. In addition, it is one of the key factors that reduce the system efficiency. So, it is necessary to analyze the current ripple in the system and maintain it at a low level. In this paper, a brief review on the different kinds of converters used in vehicles has been made. Then, with the help of MATLAB/SIMULINK, a simulation model of the hybrid power system based on 4-phase interleaved parallel topology is established.

Velocity is one of the most important inputs of active safety systems such as ABS, TCS, ESC, ACC, AEB et al. In a distributed drive electric vehicle equipped with four in-wheel motors, velocity is hard to obtain due to all-wheel drive, especially in wheel slipping conditions. This paper focus on longitudinal velocity estimation of the distributed drive electric vehicle. Firstly, a basic longitudinal velocity estimation method is built based on a typical Kalman filter, where four wheel speeds obtained by wheel speed sensors constitute an observation variable and the longitudinal acceleration measured by an inertia moment unit is chosen as input variable. In simulations, the typical Kalman filter show good results when no wheel slips; when one or more wheels slip, the typical Kalman filter with constant covariance matrices does not work well. Therefore, a gain matrix adjusting Kalman filter which can detect the wheel slip and cope with that is proposed.

In this paper, in order to avoid the frequent switching of engine operating points and improve the fuel economy during driving, this paper proposes a control strategy for the 4-wheel drive (4WD) hybrid vehicle based on wavelet transform. First of all, the system configuration and the original control strategy of the 4WD hybrid vehicle were introduced and analyzed, which summarized the shortcomings of this control strategy. Then, based on the analyze of the original control strategy, the wavelet transform was used to overcome its weaknesses. By taking advantage over the superiority of the wavelet transform method in multi signal disposition, the demand power of vehicle was decomposed into the stable drive power and the instantaneous response power, which were distributed to engine and electric motor respectively. This process was carried out under different driving modes.

It is becoming an increasingly important issue to improve NVH performance of electric drive motor for electric vehicle as the market grows rapidly. The correlation between stiffness of rear cover of motor, rotor eccentricity and noise of an electric drive is discussed in this paper which was few mentioned before. Poor stiffness of bearing chamber of rear cover may cause rotor eccentricity, which would lead to additional orders of electromagnetic noise. Stiffness optimization model of rear cover of motor was established, and the Optistruct of Hyper works software was used to improve stiffness as well as mode frequency by designing circular and radial ribs to surround bearing chamber of rear cover under guidance of topology. As compared to basis model with same mass, the 1st and 2nd strict mode frequencies of optimized rear cover separately increased by 11% and 12.5% with numerical simulations.

As the electric vehicle market grows rapidly, thermal analysis related to the performance of electric drive motors has gained increasing interest. However, it is hard to obtain rotor temperature for torque correction during operation which leads to unexpected inaccurate control of motors. Rotor temperature monitoring and torque correction for IPMSM (Interior Permanent Magnet Synchronous motor) of new Energy vehicles are discussed in this paper. Considering the practical application, a low-order lumped parameter thermal network (LPTN) composed of three nodes is built for calculating the rotor temperature under different operating conditions on a 160kw IPMSM of a three-in-one electric drive. To identify the parameters of LPTN, the measurements were done on a test bench with a prototype of the three-in-one electric drive. K-type thermocouples were used to directly measure the temperature of each node.

SEAT Department of SAIC Motor Vehicle Company starts innovatively applying the single motor and P2.5 configuration scheme from EDU G2(Electric Drive Unit Generation 2), which consists of six engine gears and four motor gears. EDU G2 is very compact and adaptable through the coupling design. Gear coupling make the engine and motor coordination limited, so as to the high efficiency zone of the engine and the high efficiency zone of the motor cannot match in some working conditions, which affect the performance of the vehicle. Therefore, SEAT developed the second generation of single-motor plug-in hybrid system EDU G2 Plus EDU G2(Electric Drive Unit Generation 2 Plus), which realized the decoupling design of 5 engine gears and 2 motor gears, so that the power output of engine and motor is freely. With excellent power and economic performance, the vehicle has been well received by customers.

Compared with the low-frequency ignition order of mechanical and combustion noise of an internal combustion engine, the noise of electric drive assembly of electric vehicles is mainly the high-frequency whining noise generated by electromagnetic forces of motors and gear meshing of reducers, as well as the high-frequency umbrella-shape noise generated by DC/AC pulse width modulation. Although the radiated sound power of these high frequency noise is far less than that of an internal combustion engine, the high frequency noise of the motor and the reducer is subjectively quite annoying. This paper studies the characteristics of electromagnetic noise of a permanent magnet synchronous motor in an electric car. By testing and analyzing of noise sources of an electric motor in the car and on a test rig, the spatial order characteristics and amplitude-frequency characteristics of the electromagnetic forces are revealed. The noise orders are multiples of the number of motor poles.

The design method for the powertrain mounting system in internal combustion engine vehicles is well-established. Electric vehicles experience higher vibration frequencies and more significant transient responses when accelerating or braking than fuel vehicles due to their high speed and fast response. Therefore, the design of the electric drive assembly mounting system requires further development. The modeling of electric drive assembly mounting systems often neglects the mounting bracket’s influence, which significantly affects the center of mass and rotational inertia of the electric drive assembly. This paper examines the effect of the mounting bracket in the electric drive assembly mounting system. It establishes a mathematical model with six degrees of freedom for the mounting system, considering the mounting bracket. By comparing the natural characteristics and the transient response, it is discussed whether the mass of the mounting bracket greatly influences the system.

With the increase of motor speed and the deterioration of operating environment, it is more difficult to predict the transient temperature field (TTF). Meanwhile, it is difficult to obtain the temperature test dataset of key nodes under various complete road conditions, so the cost of bench test or real vehicle test is high. Therefore, it is of great significance to establish a high fidelity, lightweight temperature prediction model which can be applied to real vehicle thermal management for ensuring the safe and stable operation of motor. In this paper, a physical model simulating electromagnetic-heat-flow multi-physical coupling of permanent magnet synchronous motor (PMSM) in electric drive gearbox (EDG) is established, and the correctness of the model is verified by the actual EDG bench test.

Aiming at the problem of "mileage anxiety" caused by the inaccurate estimation of vehicle owners due to the complicated and changeable actual driving conditions, the current study of electric driving range prediction focuses on exploring the battery parameters or fitting the linear relationship between electric vehicle SOC (state of charge) and driving range under ideal conditions of experiments or software simulation, which ignores the actual vehicle driving conditions and the difference in driving range due to differences in driver's driving behaviors. This paper puts forward an innovative prediction model of the driving mileage of pure electric vehicles based on driver's driving behavior.

Accurate prediction temperature variation of electric drive transmission (EDT) can effectively monitor its abnormal temperature rise that may occur under high speed and heavy load working conditions, so as to ensure the vehicles’ safe operation. In this paper, combined with real temperature and input/output characteristic data collected from EDT test platform under different working conditions, a spatio-temporal relationship dynamic graph convolution neural network based on least square method (OLS-DRGCN) for temperature prediction is proposed. Firstly, OLS is used to estimate the EDT’s internal temperature based on partial sensor information as the input of OLS-DRGCN. Secondly, the spatial dependence relationship of each temperature node is dynamically learned through node embedding and the dynamic thermal network topology of EDT is constructed. Meanwhile, the timing rule of each temperature node is obtained through the gated recurrent unit.

Multiple actuators equipped in electric vehicles, such as four- wheel steering (4WS) and four-wheel drive (4WD), provide more degrees of freedom for chassis motion control. However, developing independent control strategies for distinct actuator types could result in control conflicts, potentially degrading the vehicle's motion performance. To address this issue, a model predictive control (MPC) based steering-drive cooperated control strategy for enhanced agility and stability of electric vehicles with 4WD and 4WS is proposed in this paper. By designing the control constraints within the MPC framework, the strategy enables single-drive control, single-steering control, and steering-drive cooperative control. In the upper control layer, a linear time-varying MPC (LTV-MPC) is designed to generate optimal additional yaw moment and additional steering angles of front and rear wheels to enhance vehicle agility and lateral stability.

In view of the vibration and noise problem in the electric drive system, the vibration characteristics of its high-speed reducer are analyzed and studied. Through the vibration and noise bench test of the integrated electric drive system, the contribution of high-speed reducer gear meshing order vibration noise to the vibration noise of the electric drive system was studied. A rigid-flexible coupling dynamic model of high-speed reducer was established, and the accuracy of the model was verified. At the same time, based on the gear modification theory, the effects of different gear modification parameters on the peak-to-peak value of high-speed reducer gear transmission error, the amplitude of each order harmonic of the transmission error, and the vibration acceleration response of the high-speed reducer shell surface were studied. Genetic algorithm was used to optimize the gear modification parameters, and the optimization method was simulated and verified.

In the process of automobile industrialization, integrated electric drive systems turn to be the mainstream transmission system of electric vehicles gradually. The main sources of noise and vibration in the chassis are from the gear reducer and motor system, as a replacement of engine. For improving the electric vehicles NVH performance, effective identification and quantitative analysis of the main noise sources are a significant basis. Based on the rotating hub test platform in the semi-anechoic chamber, in this experiment, an electric vehicle equipped with a three-in-one electric drive system is taken as the research object. As well the noise and vibration signals in the interior vehicle and the near field of the electric drive system are collected under the operating conditions of uniform speed, acceleration speed, and coasting with gears under different loads, and the test results are processed and analyzed by using the spectral analysis and order analysis theories.