Variable gain control-based acceleration slip regulation control algorithm for four-wheel independent drive electric vehicle

In order to improve the dynamic performance and stability of general acceleration slip regulation (ASR) control technology for four-wheel independent drive electric vehicle (4WID EV), an ASR control strategy based on variable gain controller (VGC) is proposed in this paper. First of all, a road identification strategy is designed to identify the current road surface and calculate the optimal slip ratio of the road. Then, the optimal slip ratio is taken as the control target, and the ASR control strategy based on VGC is designed to keeps slip ratio around the optimum slip ratio through controlling the driving torque output, so wheels can make the best of road adhesion to prevent vehicle from slipping. Meanwhile, we analyze the control system state space, and build a scalar function of the system, and prove that the system satisfies Lyapunov large scale asymptotic stability theorem, so the parameters of the VGC does not affect the system stability. Then, in order to meet the requirement of quick dynamic response and no overshoot, parameters selection of VGC is deduced by mathematics. Finally, the co-simulation of Matlab/Simulink and Carsim results show that the proposed control strategy is with the better dynamics and stability, and can better prevent wheel slipping on various roads.

Research on dual-wheel-independent-drive control of electric forklift based on optimal slip ratio

Introduction: As an important transportation, the research on the control strategy of forklift has not been widely carried out. Objectives: This article proposes a turning slip regulation control strategy, which includes the improved electronic differential velocity control and turning slip regulation control, to track the optimal slip ratio. Methods: First, combined with the basic structure and characteristics of dual-wheel-independent-drive electric forklift, the vehicle model, Ackermann–Jeantand steering model, tire-ground model, and tire model of the driving wheel are established respectively. Second, according to these models, an improved electronic differential control strategy considering the influence of vertical load on tire force is proposed and it can reasonably allocate the driving torque of the two driving wheels of electric forklift. Moreover, the optimal slip ratio is given out and the turning slip regulation control strategy, which can track the optimal slip ratio of electric forklift under the conditions of different road surfaces is designed. Results: The simulation result and vehicle test show that the control strategy can optimize the slip ratio of electric forklift and greatly improve the stability of electric forklift. Conclusion: The turning slip regulation control strategy can be implemented on the TFC35 forklift to improve the safety and stability.

A state observation and torque compensation–based acceleration slip regulation control approach for a four-wheel independent drive electric vehicle under slope driving

Wheel slipping of four-wheel independent drive electric vehicle on slope will reduce vehicle controllability and driving stability, thereby reducing vehicle safety. In order to solve the problem of wheel slipping and optimize the speed control performance of four-wheel independent drive electric vehicle on slope, an acceleration slip regulation control strategy of slope drive is proposed in this paper. First, we design a road identification algorithm to identify the current road conditions of the four-wheel independent drive electric vehicle, and calculate the optimal slip ratio of the current road surface by curve fitting method. Then, with the optimal slip ratio as the control objective, the acceleration slip regulation control strategy is designed to maximize the utilization of wheel adhesion coefficient to prevent wheel slip. Third, a slope identification algorithm based on Luenberger state observer is designed to identify the various slopes of the uphill and downhill road, after which a torque compensation algorithm is designed according to the identification slope, to compensate for the longitudinal component of vehicle gravity at different slopes. Fourth, a slope torque distribution algorithm is proposed based on acceleration slip regulation and slope identification. Finally, through the joint simulation platform of MATLAB/Simulink and CarSim, it is shown that the proposed control strategy can better restrain wheel slipping on the uphill and downhill road, and has better dynamic characteristics and stability.

Model Predictive Controller-Based Optimal Slip Ratio Control System for Distributed Driver Electric Vehicle

The slip ratio control is an important research topic in in-wheel-motored electric vehicles (EVs). Traditional control methods are usually designed for some specified modes. Therefore, the optimal slip ratio control cannot be achieved while vehicles work under various modes. In order to achieve the optimal slip ratio control, a novel model predictive controller-based optimal slip ratio control system (MPC-OSRCS) is proposed. The MPC-OSRCS includes three parts, a road surface adhesion coefficient identifier, an operation mode recognizer, and an MPC based-optimal slip ratio control. The current working road surface is identified by the road surface adhesion coefficient identifier, and a modified recursive Bayes theorem is used to compute the matching degree between current road surfaces and reference road surfaces. The current operation state is recognized by the operation mode recognizer, and a fuzzy logic method is applied to compute the matching degree between actual operation state and reference operation modes. Then, a parallel chaos optimization algorithm (PCOA)-based MPC is used to achieve the optimal control under various operation modes and different road surfaces. The MPC-OSRCS for EV is verified on simulation platform and simulation results under various conditions to show the significant performance.

Design and analysis of output feedback constraint control for antilock braking system based on Burckhardt’s model

Purpose The purpose of this study is to improve vehicles’ brake stability, the problem of constraint control for an antilock braking system (ABS) with asymmetric slip ratio constraints is concerned. A nonlinear control method based on barrier Lyapunov function (BLF) is proposed not only to track the optimal slip ratio but also to guarantee no violation on slip ratio constraints. Design/methodology/approach A quarter vehicle braking model and Burckhardt’s tire model are considered. The asymmetric BLF is introduced into the controller for solving asymmetric slip ratio constraint problems. Findings The proposed controller can implement ABS zero steady-state error tracking of the optimal wheel slip ratio and make slip ratio constraints flexible for various runway surfaces and runway transitions. Simulation and experimental results show that the control scheme can guarantee no violation on slip ratio constraints and avoid self-locking. Originality/value The slip rate equation with uncertainties is established, and BLF is introduced into the design process of the constrained controller to realize the slip rate constrained control.

Design and Analysis of Output Feedback Constraint Control for Antilock Braking System with Time-Varying Slip Ratio

This paper is concerned with the problem of constraint control for an Antilock Braking System (ABS) with time-varying asymmetric slip ratio constraints. A quarter vehicle braking model with system uncertainties and a Burckhardt’s tire model are considered. The Time-varying Asymmetric Barrier Lyapunov Function (TABLF) is embedded into the controllers for handling the time-varying asymmetric slip ratio constraint problems. Two adaptive nonlinear control methods (TABLF1 and TABLF2) based on TABLF are proposed not only to track the optimal slip ratio but also to guarantee no violation on the slip ratio constraints. Simulation results show that the proposed controllers can guarantee no violation on slip ratio constraints and avoid self-locking. In the meantime, TABLF1 controller can achieve a faster convergence rate, shorter stopping time, and shorter distance, compared to TABLF2 controller with the same control parameters.