Abstract
A direct yaw moment control (DYC) system based on variable universe fuzzy logic is proposed to improve the stability of distributed drive electric vehicle in this paper. The upper layer of controller is a two-stage variable universe fuzzy controller, and the deviation between actual value and reference of yaw rate and side slip angle is used to calculate the required yaw moment. The lower layer of the controller adopts the redistribution pseudo inverse (RPI) algorithm, which takes the tire utilization rate as the optimization target and the maximum driving torque of the motor as the constraint target, and effectively distributes the required yaw moment to each wheel. The proposed control system is simulated and verified under J-turn and single shift line condition, and the control effect is reflected by comparison control in the uncontrolled, fuzzy PI control and variable universe fuzzy control. The simulation results show that it can make the vehicle track the reference better and enhance vehicle’s handing and stability, and that the control algorithm is effective and feasible.
The Project was Supported by the Key Laboratory of Expressway Construction Machinery of Shaanxi Province, 300102259513.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Habib, S., Khan, M.M., Abbas, F., et al.: A comprehensive study of implemented international standards, technical challenges, impacts and prospects for electric vehicles. IEEE Access 6, 13866–13890 (2018)
Zhai, L., Sun, T., Wang, J.: Electronic stability control based on motor driving and braking torque distribution for a four in-wheel motor drive electric vehicle. IEEE Trans. Veh. Technol. 65, 4726–4739 (2016)
Zhang, G., Zhang, H., Huang, X., et al.: Active fault-tolerant control for electric vehicles with independently driven rear in-wheel motors against certain actuator faults. IEEE Trans. Control Syst. Technol. 1–16 (2015)
Zhou, H., Chen, H., Ren, B., et al.: Yaw stability control for in-wheel-motored electric vehicle with a fuzzy PID method. In: 2015 27th Chinese Control and Decision Conference (CCDC). IEEE (2015)
Li, H., Zhihong, M., Jiayin, W.: Variable universe stable adaptive fuzzy control of nonlinear system. Sci. Chin. Ser. E Technol. Sci. 45(3), 225–240 (2002)
He, P., Hori, Y.: Optimum traction force distribution for stability improvement of 4WD EV in critical driving condition. In: 2006 9th IEEE International Workshop on Advanced Motion Control. IEEE (2006)
Abe, M., Mokhiamar, O.: An integration of vehicle motion controls for full drive-by-wire vehicle. Proc. Inst. Mech. Eng. Part K: J. Multi-Body Dyn
Guvenc, B.A., Bunte, T., Odenthal, D., et al.: Robust two degree-of-freedom vehicle steering controller design. IEEE Trans. Control Syst. Technol. 12(4), 627–636 (2004)
Sadri, S., Wu, C.Q.: Lateral stability analysis of on-road vehicles using the concept of Lyapunov exponents. In: IEEE Intelligent Vehicles Symposium (2012)
Zhang, B., Du, H., Lam, J., et al.: A novel observer design for simultaneous estimation of vehicle steering angle and sideslip angle. IEEE Trans. Ind. Electron. 63(7), 1 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Cao, S., Wang, Y., Jia, H., Zhang, Z. (2019). Variable Universe Fuzzy Control for Direct Yaw Moment of Distributed Drive Electric Vehicle. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11743. Springer, Cham. https://doi.org/10.1007/978-3-030-27538-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-27538-9_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27537-2
Online ISBN: 978-3-030-27538-9
eBook Packages: Computer ScienceComputer Science (R0)