Research on the Anti-Disturbance Control Method of Brake-by-Wire Unit for Electric Vehicles

Abstract

In order to improve the braking performance of electric vehicles, a novel brake-by-wire actuator based on an electro-magnetic linear motor was designed and manufactured. For the purpose of braking force regulation accuracy and high robust performance, the state observer and the anti-disturbance controller were designed in this paper after describing the actuator structure, braking principle, and mathematical model. The simulation and experimental results showed that the brake actuator responded rapidly, since its response time was only 15 ms. Compared to traditional PID (Proportion Integration Differentiation) methods, the controller proposed in this paper is able to regulate the braking force more precisely and has better anti-disturbance performance, thus the braking process can be accurately controlled according to the driver’s demand. The vehicle simulation results showed that the braking distance and braking time were shortened by 12.19% and 15.54%, respectively compared with those of the conventional anti-lock brake system (ABS) in the same braking conditions.

Review on the Development, Control Method and Application Prospect of Brake-by-Wire Actuator

“…The state observer and double closed-loop anti-disturbance control algorithm were used to regulate the braking force. The experimental results show that the actuator response time is less than 15 ms and the braking force can be accurately adjusted, which indicates that it has good performance [46]. The robust fractional order controller (CRONE) has low sensitivity to noise and good robustness to challenges, such as parameter uncertainty, nonlinearity, and disturbance.…”

“…The research process is mainly divided into two steps: simulation and test verification. In the simulation phase, the professional software, such as Maxwell, AMESim, and Simulink, are used to establish the actuator's finite element model, dynamic model, and controller model, and the analysis tools and optimization theories are used to optimize the actuator and controller [26,46]. In the test phase, dSPACE is firstly used to complete software-in-the-loop (SIL) and hardware-in-the-loop (HIL) verification; and then, the actual vehicle test is completed to comprehensively evaluate the BBW system [9,10,47,48].…”

“…There are two ways to obtain the caliper clamping force: direct measurement and indirect estimation. The EHB and hybrid BBW actuator can directly measure caliper force by measuring hydraulic pressure, and the Kalman filter can also be used to eliminate the sensor measurement noise and improve the data accuracy [46]. For indirect estimation, the caliper force is usually estimated from the piston position.…”

“…In order to accurately estimate the caliper force, Todeschini designed a "position-pressure switching controller" to address the highly non-linearity between the piston position and hydraulic pressure [34], and adopted an adaptive algorithm to reduce the estimation error that is caused by temperature changes and friction plate wear [35]. There are also literatures that use estimation algorithms to estimate the hydraulic pressure change rate that cannot be indirectly measured and provide more feedback variables to the controller [46].…”

Electric Vehicle Sales Catastrophe Averted (?)

“…An interesting manuscript "The effect of perceived risk on the purchase intention of electric vehicles: an extension to the technology acceptance model" (Thilina, 2019) seeks to analyze significant market penetration for the sale of electric vehicles accompanied by the analysis (Mo, 2018) of life-cycle cost of ownership including congestion and environmental impacts (Tu, 2019), (Rajeev, et al, 2019), (Hao, 2017), (Philipsen, et al, 2019), (Lopez-Arboleda, et al, 2019), (Almeida, et al, 2019). Considerable emphasis have been placed on improvements in vehicle charging (Wolbertus, et al, 2019) amongst many other underlying technological areas seeking to improve the value proposition to potential buyers (Jager, et al, 2019), , , (Minnerup, et al, 2019), (Muller, 2019) and also make recommendations in both technology (Zha, et al, 2019), , (Zha, et al, 2019), , (Jiyan, et al, 2019), (Pier, et al, 2019), (Agaton, et al, 2019), , (Watanabe, et al, 2019), (Kusaka, et al, 2019), (Zhang, W., et al, 2019), , (Mayer, et al, 2019), (Ricciardi, et al, 2019), , (Yu, Z., et al, 2019), (Senda, et al, 2019), (Marquez-Fernandez, et al, 2019), (Wu, D., et al, 2019), (Wang, H., et al, 2019), (Obayashi, et al, 2019), (Gong, et al, 2019), (Vermeulen, et al, 2019), (Jia, J., et al, 2019), (Li, Q., et al, 2019) and policy incentives (Zhang, X., et al, 2019), (Ortar, et al, 2019), culminating in charging strategies to influence the obvious trade-off between gasoline prices and charging availability , (Wolbertus, et al, 2019),…”