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Thanks to the actuation flexibility of their systems, electric vehicles with individual powertrains, including in-wheel and on-board motors, are a very popular research topic amongst various types of electrified powertrain architectures. The introduction of the individual electric powertrain provides great capacity for improvement of the vehicle’s energy efficiency and control performance. However, it also poses tremendous challenges concerning vehicle safety, due to the complex system dynamics and cooperation mechanisms between multiactuators. For an electric vehicle with independently controlled motors, because of design and manufacturing factors, the steady-state error of each motor output torque, and the flexibilities and nonlinear backlash of left and right drivetrains, can be different. This results in asymmetrical output characteristics of electric powertrain systems on the same axle.

In order to realize the series-parallel switching control of hybrid electric vehicle (HEV) with dual-motor hybrid configuration, a method of unpowered interrupt switching based on the coordinated control of three power sources was proposed by analyzing the series-parallel driving mode of the dual-motor hybrid configuration. The series to parallel switching process is divided into three stages: speed regulation stage, clutch combination and power source switching. The distribution control of speed regulating torque is carried out in the speed regulating stage. The speed adjustment torque is preferentially allocated to the power source of the input shaft (engine and P1) to carry out the lifting torque. Due to the high speed adjustment accuracy and fast response of the P1 motor, the input shaft is preferentially allocated to P1 for speed adjustment, that is, the torque intervention of P1.

In order to realize the shift control of dual-motor hybrid electric vehicle (HEV), a non-power interruption shift control method based on three-power source coordination control was proposed by analyzing the shift process of dual-motor hybrid configuration. The shift control process was divided into three stages: oil-filling self-learning stage, torque exchange stage and inertia control stage. In the torque exchange stage, the characteristics of the speed stage and torque stage were analyzed, which was different from the traditional method's dependence on pressure sensor, longitudinal acceleration sensor and engine torque accuracy. A shift clutch gain self-learning strategy based on shift time and input shaft speed soaring problem was proposed.

DHT hybrid transmission assembly control system discussed in this paper includes hydraulic control, hybrid mode switching control, shift control, dual motor control, clutch and motor thermal management. The hybrid mode is divided into four modes: the EV mode, the serial mode, the parallel mode and the launch mode. Hydraulic control includes torque-pressure conversion, clutch pressure kiss point adaption, clutch oil filling time adaption. Shift control includes shift type decision, shift sequence control, shift inertia process based on motor intervention. Thermal management includes clutch flow and motor flow distribution. Motor control include the current control, mode control and boost strategy of permanent magnet synchronous motor in dual hybrid system, which has good stability and robustness. Motor mode includes initialization mode, normal mode, fault mode, active discharge mode, power off mode.

In hybrid vehicles, the drive motor is directly connected to the drive train and the inherent drive train damping is low. When subjected to external disturbance, the low damping characteristics of the transmission system may cause torsional vibration, which will continue to oscillate the transmission system and affect the driving performance of the vehicle. In this paper, we propose a harmonic injection wheel control method based on motor speed to suppress oscillations and improve the driving performance of hybrid electric vehicles. The harmonic injection control method based on motor speed is based on Fourier transform to decompose sinusoidal harmonics based on specific order of motor speed. RLS algorithm is used to estimate the amplitude and phase, and PI control is used to calculate the compensation torque for the actual amplitude and target amplitude. Simulation and test results show that the proposed control strategy is effective in suppressing oscillations.

In order to solve the problems of the shuffle caused by internal and external excitation and the difficulty in obtaining the real-time accurate engine torque during the parallel mode operation of hybrid electric vehicles, a dynamic coordination control strategy for suppressing the jitter of hybrid electric vehicles based on the closed-loop control of engine speed was proposed. The engine torque filtering control method based on the slope limit was adopted to limit the rate of change of the engine torque and reduce the impact caused by the sudden change of the engine torque; the engine speed closed-loop control method was used to take the motor speed which is easy to be measured accurately in real time as the feedback control variable, which solved the problem of the real-time accurate estimation of the engine torque online. In parallel mode, the motor torque accounts for a small proportion because the torque distribution method gives priority to the engine.

With the rise of new energy vehicle industry as a national strategy, China has gradually occupied an absolute leading position in the field of battery electric vehicles, especially commercial battery electric vehicles, and has taken the lead in the research and development of dual-motor coupling propulsion technology. Due to the complex and diversiform structure of multi-source power speed-variable propulsion system, there is no mature configuration and technical details. Also, the control problem is a typical hybrid system problem, and there is no unified and clear problem description and solution method. In addition, the current research on the mode switching derived from the novel electrified powertrain is not deep enough to fully explore the potential advantages of electromechanical driveline, and there is a certain research blank considering the online implementation.

A novel type of regenerative braking system for electric vehicles is proposed in this paper. Four pressure-difference-limit valves, two relief valves and two brake pedal simulators, are added to the layout of a conventional four-channel hydraulic modulator. The cooperation of relief valves and hydraulic pumps provides a stabilized high-pressure source. Pressure-difference-limit valves ensure that the pressure in each wheel cylinder can be modulated separately at a high precision. Besides, the functions of anti-lock braking system and electronic stability program are integrated in this regenerative braking system. The models of regenerative braking controller and vehicle dynamics are built in MATLAB/Simulink. Hydraulic brake model is built in AMESim through a parameterized and modularized method. Meanwhile, the control strategy of hydraulic brake modulation and brake force distribution are designed.

In this paper, gear ratios of a two-speed transmission system are optimized for an electric passenger car. Quasi static system models, including the vehicle model, the motor, the battery, the transmission system, and drive cycles are established in MATLAB/Simulink at first. Specifically, since the regenerative braking capability of the motor is affected by the SoC of battery and motors torque limitation in real time, the dynamical variation of the regenerative brake efficiency is considered in this study. To obtain the optimal gear ratios, iterations are carried out through Nelder-Mead algorithm under constraints in MATLAB/Simulink. During the optimization process, the motor efficiency is observed along with the drive cycle, and the gear shift strategy is determined based on the vehicle velocity and acceleration demand. Simulation results show that the electric motor works in a relative high efficiency range during the whole drive cycle.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

This paper presents a coordinated controller for comprehensive optimization of vehicle dynamics performance and energy consumption for a full drive-by-wire electric vehicle, which is driven by a four in-wheel motor actuated (FIWMA) system and steered by a steer-by-wire (SBW) system. In order to coordinate the FIWMA and SBW systems, the mechanisms influencing the vehicle dynamics control performance and the energy consumption of the two systems are first derived. Second, the controllers for each subsystem are developed. For the SBW system, a triple-step control technique is implemented to decouple the yaw rate and sideslip angle controls. The FIWMA system controller is designed with a hierarchical control scheme, which is able not only to satisfy the yaw rate and sideslip angle tracking demands, but also to deal with actuation redundancy and constraints.