Feature extraction and recognition: key to solving stability issues in electric braking booster

Mingming Mei; Shuo Cheng; Hongyuan Mu; Zhuoqiang Li

doi:10.1117/12.2685062

19 October 2023 Feature extraction and recognition: key to solving stability issues in electric braking booster

Mingming Mei, Shuo Cheng, Hongyuan Mu, Zhuoqiang Li

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127090W (2023) https://doi.org/10.1117/12.2685062
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

As the E-Booster is widely used, its stability and safety are receiving more and more attention. However, the nonlinear characteristics causes interference in describing the system characteristics. In this paper, a nonlinear least squares (NLS) method is proposed to extract the hydraulic characteristics, and then the control is corrected by predicting idle stroke to improve the performance. First, the reasons that lead to the deterioration of the braking performance after the vehicle passes over a washboard surface are analyzed. The open-loop system gain is changed due to the increase in clearance, and it is demonstrated that the system performance becomes worse or even unstable with the help of Nyquist plots and describing functions. A piecewise linear function with three parameters is then proposed to characterize the dynamic system. From a complete period of increase and decrease in pressure, the parameter values can be obtained by NLS. Taking the three parameters as input, the support vector machine (SVM) and neural network (NN) methods are used to predict the current idle stroke. Finally, the simulation results show that NN has higher classification accuracy and better generalization capability. The nonlinear compensation to the controller can significantly improve the performance of the system.

Citation Download Citation

Mingming Mei, Shuo Cheng, Hongyuan Mu, and Zhuoqiang Li "Feature extraction and recognition: key to solving stability issues in electric braking booster", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127090W (19 October 2023); https://doi.org/10.1117/12.2685062

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available