Hierarchical braking accurate control of electrohydraulic composite braking system for electric vehicles

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Jun-Cheng Wang
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引用次数: 0

Abstract

For the electrohydraulic composite braking system, the general total braking force calculation strategy frequently ignores the resist forces, thereby cannot track the braking intention of driver perfectly. Moreover, the torque allocation process reduces the control reliability and energy recovery effect. In this research, a novel hierarchical braking accurate control (HBAC) algorithm is designed to achieve both the control accuracy and the ideal energy recovery efficiency. It includes target calculation, parameter adjustment, and organization coordination levels. In the target calculation level, the resist forces such as air, tire roll resistances are considered to calculate the demanded-braking force accurately. In the parameter adjustment level, the ideal demand-braking force is constrained by the estimated road adhesion coefficient and the vertical load transfer. At the organization coordination level, the torque allocation process is omitted by applying a compensation control of the hydraulic braking torque. The simulation results indicated outstanding braking distances by the proposed HBAC are 111.5 m, 40.8 m, and 63.2 m under the varying adhesion, dry asphalt, and wet asphalt roads, respectively. Moreover, compared with the comparative control strategy, the energy recovery efficiency of HBAC is increased by 11.74 %, 6.67 %, and 8.4 % under these road conditions. Experimental implementation corroborates the effectiveness of proposed strategy.
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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