Affiliation:
1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China e-mail:
2. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Abstract
This paper presents the analysis and design of a novel traction control system (TCS) based on sliding-mode control (SMC) and maximum transmissible torque estimation (MTTE) technique, which is employed in four-wheel independent drive electric vehicles (EVs) without detecting the vehicle velocity and acceleration. The original MTTE technique is effective with regard to the antislip control; however, it cannot sufficiently utilize the adhesive force from the tire–road surface. In the proposed TCS algorithm, only front wheels are equipped with the MTTE technique, while rear wheels are equipped with the SMC technique. As a result, the front wheel is critically controlled by the MTTE technique. Thus, its rotary speed can be used to approximately estimate the chassis velocity and acceleration, which are key input parameters of the SMC. The rear wheel slip ratio can be therefore controlled by the SMC which is robust against uncertainties and disturbances of parameters for exploiting more transmissible friction force. In addition, the stability of MTTE is analyzed in this paper because an important parameter is neglected in the original MTTE technique. As a result, the stability condition is changed, and the MTTE is modified in the proposed TCS according to the new conclusion. A half four-wheel drive (4WD) EV model is initially built using matlab/simulink. This paper investigates the proposed TCS for various adhesive conditions involving abrupt change in road friction. Compared with the original MTTE technique, the comprehensive performance, particularly the acceleration ability, is significantly improved by the proposed controller. The simulation result validates the effectiveness and robustness of the proposed TCS.
Subject
Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering
Cited by
16 articles.
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