Four-wheel Independent-drive Electric Vehicle Research Articles

Adaptive Sliding Mode Control for Yaw Stability of Four-Wheel Independent-Drive EV Based on the Phase Plane

Aiming at the yaw stability problem of a four-wheel independent-drive electric vehicle (EV) during steering, this paper proposes an adaptive sliding mode control strategy (ASMC) for yaw stability based on the phase plane. The control strategy adopts hierarchical control. The upper layer is the ASMC controllers based on particle swarm optimization (PSO). Aiming at the chattering problem of sliding mode controller, the approach law is designed as the adaptive approach law, which changes with the change of system state by using the adaptive control principle; to minimize the response delay and tracking error, the control system is taken as the object to find a set of optimal parameters for a constant velocity approach rate based on PSO. The middle level is a joint controller, which uses the established β−β˙ phase plane stability region boundary model to control the upper-level controllers jointly. When the vehicle is in the stable region, the ASMC controller for the yaw rate is used to determine the yaw moment; when the vehicle is outside the stable region, the final yaw moment is determined by the ASMC controller for the yaw rate and the ASMC controller for the sideslip angle, to restore the stability of the vehicle. The lower layer is a torque optimal distribution controller, which converts the yaw moment into torque and optimally distributes it to four wheels. Finally, Simulink and CarSim platforms are used for joint simulation. The results prove that the proposed control strategy can effectively reduce the error between the actual and the ideal value of control parameters and improve the vehicle’s stability when steering.

Chassis coordinated control based on ideal roll angle to improve vehicle stability

The current active control system for vehicles mainly focuses on following the reference trajectory constituted by the ideal yaw rate and sideslip angle, without considering the influence of the body roll angle on the vehicle stability performance. To improve the vehicle stability, in this study, a method of determining the three-dimensional stability region of ‘lateral speed–yaw rate–roll angle’ was proposed, the variation of the stability region with respect to the front steering angle was studied, and the limit steering angle boundary and vehicle ideal roll angle were obtained. Subsequently, a hierarchical coordinated control framework was proposed for actively controlling the front steering angle, suspension force, and motor torque of a four-wheel independent-drive electric vehicle with active front steering and active suspension systems. Finally, considering the effects of different motor torque distribution algorithms on the control performance, the performance of several control strategies was compared for high and low adhesion roads. The results indicated that the control strategy considering the body roll angle under different working conditions can improve the vehicle stability. On this basis, the torque distribution strategy based on minimum tire utilisation has the best following and stability performances among the strategies examined in this study.

Parameter influence analysis in an optimized fuzzy stability control for a four-wheel independent-drive electric vehicle

This paper presents an optimized fuzzy logic control (FLC) applied to four-wheel independent-drive electric vehicles (FWID-EVs). The controller is developed to act as an Electronic Differential (ED), which changes the in-wheel motors torques to correct the vehicle trajectory during some specific maneuvers. The simulation determines the rotation, the lateral and longitudinal displacement of the vehicle, in which the nonlinear Magic Formula is applied to define the tires slip, associated with the load transfer during curves or drive/break situations and with the steering input. According to the literature, several parameters are used to provide stability controls of similar vehicles, for example, the sideslip angle and yaw rate. Therefore, a parameter influence analysis is carried out to find out the most relevant parameters to be monitored in the investigated FWID-EV. Once the relevant input parameters are defined, an optimum ED FLC is developed by means of a genetic algorithm multi-objective optimization with the objective of minimizing the trajectory error of the FWID-EV under a combination of the Sine with Dwell and constant steering standard maneuvers. The results show the best control configuration is a combination of steer and sideslip angles, with a reduced number of rules and less processing time (0.71 s). Besides, the proposed control presents a reduction in the trajectory error, improvement up to 95.1%, emphasizing that the parameter influence analysis allows finding an optimum, more efficient, and time-saving control solution. Therefore, a simple adjustment in the variables inputs can decrease the control process, without overshadowing the dynamic behavior.

Electric vehicle powertrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle

The four-wheel independent-drive electric vehicle (FWID-EV) stands out among the electrically-propelled vehicles due to its higher efficiency. This EV configuration faces an energy management challenge, needing a controller to define the best power split among the motors, decreasing the energy consumption while keeping the EV performance. Aiming to overcome this challenge, this paper presents a fuzzy logic control (FLC) strategy to perform the power split among the electric motors to improve vehicle energy efficiency and dynamic performance under real driving conditions. The implemented controller is developed hierarchically, ensuring the speed follows a driving cycle and acting as an electronic differential to correct the vehicle trajectory along the path. Multi-objective optimization is presented using a particle swarm algorithm (MOPSO) to minimize the mass of the electrical components (motors and battery) and extend the driving range throu gh the maximization of the battery state of charge (SoC). Moreover, the optimization process also aims to enhance vehicle handling by minimizing the driver steering input during the cycle. The best trade-off solution was able to reach a 124.2 km drive range with a 235.8 kg battery (387.8 V and 91.2 Ah), presenting improved handling performance with 78.5% decrease in the driver steering action.

Wheel torque distribution optimization of four-wheel independent-drive electric vehicle for energy efficient driving

With the help of several in-wheel motors, four-wheel independent-drive electric vehicle (4WIDEV) has tremendous potential to improve vehicle performance. Except for the theme of stability enhancement during the past two decades, energy saving topic becomes more attractive recently. However, it is difficult to achieve stability and economy performance simultaneously. Given the commonly used control method of rigid yaw rate tracking may limit the energy saving potential of 4WIDEV in cornering. Therefore, be different from previous studies which often focus on a sole target, in this paper, a driving energy management strategy for 4WIDEV based on multi-objective online optimization of four-wheel torque distribution is proposed in this paper, which includes weighted yaw rate tracking error into its parameterized control objectives besides electric drive system efficiency, tire slip losses and wheel torque ripple. Meanwhile, for better coordination of stability and economy in different situation, fuzzy logic control is adopted to dynamically adjust the weight of the control objective indexes of the proposed multi-objective online optimization function. Then, a particle swarm optimization algorithm is adopted to solve the optimization function. Finally, the proposed strategy for energy-efficient driving is verified based on the built Simulink and CarSim co-simulation model. The results show that the proposed four-wheel torque distribution strategy based on the multi-objective online optimization is more effective than average distribution strategy and offline optimization strategy.

Development and evaluation of torque distribution methods for four-wheel independent-drive electric vehicle based on parameter estimation

A hierarchical controller including a vehicle condition parameter estimator for improving the vehicle stability is theoretically applied to a four-wheel independent-drive electric vehicle. This stu...

An Optimal Torque Distribution Control Strategy for Four-Wheel Independent Drive Electric Vehicles Considering Energy Economy

To further improve the energy economy of a four-wheel independent drive electric vehicle (FWIDEV) in the process of vehicle stability control, in this paper, the influence of different wheel torque distributions on vehicle stability and energy economy during vehicle steering is analyzed in depth. Then the wheel torque distribution scheme when the vehicle steering is established. Combined with the economic-based torque distribution strategy applied in the straight running condition, an optimal wheel torque distribution strategy is proposed for FWIDEV to adapt different driving conditions. And the controller designed in this paper adopts hierarchical control structure. The upper controller calculate the corrective yaw moment based on the sliding mode control. The lower controller implements wheel torque distribution according to the proposed strategy. Finally, the simulation results under different driving scenarios indicate that the proposed control strategy can achieve the same effect as the conventional control strategy in terms of vehicle stability, but the energy economy is improved by about 2.4%.

Research on Torque Allocation of Four-Wheel Independent-Driving Electric Vehicles Based on Stability

AbstractA torque allocation method of PID (Proportion-Integral-Derivative) control based on BP (Back-Propagation) neural network is adopted to investigate the stability of a four-wheel independent-...

Direct yaw-moment control for 4WID electric vehicle via finite-time control technique

This paper is concerned with the yaw-moment stabilization for four-wheel independent-drive electric vehicle. A second-order sliding mode observer is first designed to estimate the required sideslip angle in a finite time. Then, the finite-time control technique and nonlinear disturbance observer are applied to construct the upper controller to drive both yaw rate and sideslip angle to their desired values. Finally, the lower controller is developed to distribute the torques to the independent four wheels according to the desired yaw moment obtained by the given upper controller. Comparisons among linear, discontinuous and nonsmooth controllers under different working conditions are given by using CarSim software.

Analysis of the Lateral Stability for Four-Wheel Independent Driving Electric Vehicles

The four-wheel independent driving EVs have been considered as the hot spot due to their excellent controlling capability of the driving force distribution in recent years. In order to achieve the excellent control capability of electric drive systems, the mechanical properties and performance need to be investigated and evaluated. In this paper, the lateral stability of four-wheel independent driving EVs is studied and the major factors are investigated. Results of the analysis indicate that the sideslip angle of the vehicle should be controlled at a small value. Under this condition, the yaw rate plays a key role on the lateral stability of the vehicle. The results in this research provide a solid guidance to considerably improve the lateral stability and the active safety of the EVs, in both theoretical and practical aspects.

Optimal Slip Ratio Based Fuzzy Control of Acceleration Slip Regulation for Four-Wheel Independent Driving Electric Vehicles

To improve the driving performance and the stability of the electric vehicle, a novel acceleration slip regulation (ASR) algorithm based on fuzzy logic control strategy is proposed for four-wheel independent driving (4WID) electric vehicles. In the algorithm, angular acceleration and slip rate based fuzzy controller of acceleration slip regulation are designed to maintain the wheel slip within the optimal range by adjusting the motor torque dynamically. In order to evaluate the performance of the algorithm, the models of the main components related to the ASR of the four-wheel independent driving electric vehicle are built in MATLAB/SIMULINK. The simulations show that the driving stability and the safety of the electric vehicle are improved for fuzzy logic control compared with the conventional PID control.