Braking performance oriented multi–objective optimal design of electro–mechanical brake parameters

Author:

Wu TongORCID,Li Jing,Qin Xuan

Abstract

Excellent braking performance is the premise of safe driving, and improve the braking performance by upgrading structures and optimizing parameters of braking systems has become the pursuit of engineers. With the development of autonomous driving and intelligent connected vehicle, new structural schemes such as electro–mechanical brakes (EMBs) have become the future of vehicle braking systems. Meanwhile, many scholars have dedicated to the research on the parameters optimization of braking systems. While, most of the studies focus on reducing the brake size and weight, improving the brake responses by optimizing the parameters, almost not involving the braking performance, and the optimization variables are relatively single. On these foundations, a multi–objective optimal design of EMB parameters is proposed to enhance the vehicle’s braking performance. Its objectives and constraints were defined based on relevant standards and regulations. Subsequently, the decision variables were set, and optimal math model was established. Furthermore, the co–simulation platform was constructed, and the optimal design and simulation analyses factoring in the crucial structural and control parameters were performed. The results confirmed that the maximum braking pressure response time of the EMB is decreased by approximately 0.3 s, the stopping distance (SD) of 90 km/h–0 is shortened by about 3.44 m. Moreover, the mean fully developed deceleration (MFDD) is increased by 0.002 g, and the lateral displacement of the body (LD) is reduced by about 0.037 m. Hence, the vehicle braking performance is improved.

Funder

the National Key R&D Program of China

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference32 articles.

1. Driving–style–based codesign optimization of an automated electric vehicle: A cyber–physical system approach;C Lv;IEEE Trans. Ind. Electron,2019

2. Hybrid–learning–based classification and quantitative inference of driver braking intensity of an electrified vehicle;C Lv;IEEE Trans. Veh. Technol,2018

3. Clamping force control of electro–mechanical brakes based on driver intentions;J Li;Plos One,2020

4. haldex–vie.cn [Internet]. Shanghai: Haldex VIE EMB; c2020 [cited 2020 Dec 19].

5. Design and optimization of a cam–actuated electrohydraulic brake system;L Durali;Proc. Inst. Mech. Eng. Part D–J. Automob. Eng,2018

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