Active fault-tolerant control and performance simulation of electric vehicle suspension based on improved algorithms

Authors

DOI:

https://doi.org/10.4108/ew.6146

Keywords:

PSO, Multiple degrees of freedom, Vehicle model, Active suspension, Robust control

Abstract

Based on the semi-active suspension controller of an automobile, the control law can be adjusted based on the control law reorganization idea, and the active fault-tolerant controller of the semi-active suspension is designed to make the fault closed loop system and the fault-free suspension semi-active suspension. Active suspension closed-loop systems have the same closed-loop pole or proximity system performance. Bench test and simulation results show that: the fault suspension under the control of the active fault-tolerant controller lags behind its performance level after some time and can quickly recover to the same performance as the fault-free automotive semi-active suspension level. And the simulation test and bench test results are basically consistent. Based on the concept of control law reorganization to design the active fault-tolerant control strategy of semi-active suspension, it can effectively realize the active fault-tolerant control of the semi-active suspension of the vehicle to improve the suspension control quality and reliability, and optimize the suspension design.

Downloads

Download data is not yet available.

References

J. A. Sanguesa, V. Torres-Sanz, P. Garrido, et al., “A review on electric vehicles: Technologies and challenges,” Smart Cities, vol. 4, no. 1, pp. 372-404, 2021. DOI: https://doi.org/10.3390/smartcities4010022

W. Zhao, Y. Wang, and C. Wang, “Multidisciplinary optimization of electric-wheel vehicle integrated chassis system based on steady endurance performance,” Journal of Cleaner Production, vol. 186, pp. 640-651, 2018. DOI: https://doi.org/10.1016/j.jclepro.2018.03.157

H. Wu, Q. Gao, C. Wang, et al., “Decoupling control of chassis integrated system for electric wheel vehicle,” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 234, no. 6, pp. 1515-1531, 2020. DOI: https://doi.org/10.1177/0954407019889225

A. R. Albrecht, Y. Wang, M. Ghasemkhani, et al., “Exploring ultrafast negative Kerr effect for mode-locking vertical external-cavity surface-emitting lasers,” Optics express, vol. 21, no. 23, pp. 28801-28808, 2013. DOI: https://doi.org/10.1364/OE.21.028801

G. A. Hassaan, “Car dynamics using quarter model and passive suspension, part I: effect of suspension damping and car speed,” International Journal of Computer Techniques, vol. 1, no. 2, pp. 1-9, 2014.

M. Tahmasebi, R. A. Rahman, M. Mailah, et al., “Sprayer boom active suspension using intelligent active force control,” Journal of World Academy of Science, Engineering and Technology, vol. 68, pp. 1277-1281, 2012.

H. E. Tseng, and D. Hrovat, “State of the art survey: active and semi-active suspension control,” Vehicle system dynamics, vol. 53, no. 7, pp. 1034-1062, 2015. DOI: https://doi.org/10.1080/00423114.2015.1037313

C. Poussot-Vassal, C. Spelta, O. Sename, et al., “Survey and performance evaluation on some automotive semi-active suspension control methods: A comparative study on a single-corner model,” Annual Reviews in Control, vol. 36, no. 1, pp. 148-160, 2012. DOI: https://doi.org/10.1016/j.arcontrol.2012.03.011

Z. Huang, A. H. Proppe, H. Tan, et al., “Suppressed ion migration in reduced-dimensional perovskites improves operating stability,” ACS Energy Letters, vol. 4, no. 7, pp. 1521-1527, 2019. DOI: https://doi.org/10.1021/acsenergylett.9b00892

M. J. Mahmoodabadi, A. A. Safaie, A. Bagheri, et al., “A novel combination of Particle Swarm Optimization and Genetic Algorithm for Pareto optimal design of a five-degree of freedom vehicle vibration model,” Applied Soft Computing, vol. 13, no. 5, pp. 2577-2591, 2013. DOI: https://doi.org/10.1016/j.asoc.2012.11.028

M. Zehsaz, F. Vakili-Tahami, A. Fasihi, et al., “Sensitivity of ride comfort to Suspension characteristics of an off-road vehicle under road excitation,” International Journal of Emerging Technology and Advanced Engineering, vol. 2, no. 5, pp. 422-431, 2012.

Y. Wang, P. Li, and G. Ren, “Electric vehicles with in-wheel switched reluctance motors: Coupling effects between road excitation and the unbalanced radial force,” Journal of Sound and Vibration, vol. 372, pp. 69-81, 2016. DOI: https://doi.org/10.1016/j.jsv.2016.02.040

C. C. J. Kuo, “Understanding convolutional neural networks with a mathematical model,” Journal of Visual Communication and Image Representation, vol. 41, pp. 406-413, 2016. DOI: https://doi.org/10.1016/j.jvcir.2016.11.003

A. Manthiram, X. Yu, and S. Wang, “Lithium battery chemistries enabled by solid-state electrolytes,” Nature Reviews Materials, vol. 2, no. 4, pp. 1-16, 2017. DOI: https://doi.org/10.1038/natrevmats.2016.103

G. Ceder, G. Hautier, A. Jain, et al., “Recharging lithium battery research with first-principles methods,” Mrs Bulletin, vol. 36, no. 3, pp. 185-191, 2011. DOI: https://doi.org/10.1557/mrs.2011.31

L. Huang, “Optimization of a new mathematical model for bacterial growth,” Food Control, vol. 32, no. 1, pp. 283-288, 2013. DOI: https://doi.org/10.1016/j.foodcont.2012.11.019

M. G. Safonov, “Origins of robust control: Early history and future speculations,” Annual Reviews in Control, vol. 36, no. 2, pp. 173-181, 2012. DOI: https://doi.org/10.1016/j.arcontrol.2012.09.001

Downloads

Published

18-07-2024

How to Cite

1.
Xiao C. Active fault-tolerant control and performance simulation of electric vehicle suspension based on improved algorithms. EAI Endorsed Trans Energy Web [Internet]. 2024 Jul. 18 [cited 2024 Nov. 9];11. Available from: https://publications.eai.eu/index.php/ew/article/view/6146