Improvement of In-Wheel Motorized Electric Vehicle Stability Through Yaw Motion Control
[1]
Ahmed Sami, Basic Science Department, Giza Engineering Institute, Giza, Egypt.
[2]
Mohammed Abd Elhafiz, Automotive and Tractors Department, Faculty of Engineering-Mataria, Helwan University, Cairo, Egypt.
[3]
Esam Morsy, Automotive and Tractors Department, Faculty of Engineering-Mataria, Helwan University, Cairo, Egypt.
[4]
Nabil Hammad, Automotive and Tractors Department, Faculty of Engineering-Mataria, Helwan University, Cairo, Egypt.
The electric vehicles are an excellent alternative to the internal combustion engine-based vehicles. One of the types of the electric vehicle is the in-wheel motorized electric vehicle which has an electric motor inside each wheel to drive the electric vehicle. These electric motors with their rapid and accurate torque control capabilities offer more opportunities for the development of electric vehicles with in-wheel electric motors. Also, the in-wheel motorized electric vehicle is a perfect platform for developing a yaw motion control system to enhance lateral stability of the electric vehicle. The most famous parameters to judge the vehicle lateral stability are the yaw rate and the body sideslip angle. So, three control techniques have been applied to study the improvement of the vehicle stability. Those techniques are: Linear Quadratic Regulator (LQR), Proportional–Integral–Derivative (PID) and Fractional order PID tuned by genetic algorithms. The simulation has been generated using MATLAB/Simulink and MSC Adams after using ISO double lane change test to simulate the behavior of the vehicle with the control systems. The simulation results prove that the Fractional order PID tuned by genetic algorithms offers the best following yaw rate and the LQR gives better limitations of the body sideslip angle.
In-wheel Motorized Electric Vehicle, Vehicle Lateral Stability, Yaw Rate, Body Sideslip Angle, LQR, PID, Fractional Order PID
[1]
Jin, L. & Liu, Y., 2014. Study on Adaptive Slid Mode Controller for Improving Handling Stability of Motorized Electric Vehicles. Hindawi Publishing Corporation, Volume 2014, pp. 1-10.
[2]
Kim, J. & Kim, H., 2007. Electric Vehicle Yaw Rate Control using Independent In-Wheel Motor. Nagoya, IEEE, pp. 705-710.
[3]
Ramprabhu, J. & Subashini, J. M., 2016. Design and stability analysis of four-in-wheel drive electric vehicle based on variable structure control algorithm. International Journal of Advances in Computer and Electronics Engineering, 10 (3), pp. 10-16.
[4]
Jalali, K., 2010. Stability Control of Electric Vehicles with In-wheel Motors. [Online] Available at: https://uwspace.uwaterloo.ca/handle/10012/5268 [Accessed 17 June 2010].
[5]
ITOH, Y., SAKAI, K. & MAKINO, Y., 2011. In-Wheel Motor System. OSAKA, Japan, NTN corporation, pp. 22-28.
[6]
Wang, R. & Wang, J., 2011. Stability Control of Electric Vehicles with Four Independently Actuated Wheels. Orlando, FL, IEEE, pp. 2511-2516.
[7]
Hasan, M. A. E., Ektesabi, M. & Kapoor, A., 2013. A Suitable Electronic Stability Control System Using Sliding Mode Controller for an In-wheel Electric Vehicle. Hong Kong, International Association of Engineers (IAENG), pp. 1-7.
[8]
Nam, K., Fujimoto, H. & Hori, Y., 2012. Lateral Stability Control of In-Wheel-Motor-Driven Electric Vehicles Based on Sideslip Angle Estimation Using Lateral Tire Force Sensors. IEEE Transactions on Vehicular Technology, Volume 61, pp. 1972-1985.
[9]
Ahmed, A. A. & Özkan, B., 2016. Simulation of Stability Control for In-Wheel Motored Vehicle Using Fuzzy PID Controller. International Journal of Advances in Mechanical & Automobile Engineering (IJAMAE), 3 (1), pp. 1-4.
[10]
Chen, B. C. & Kuo, C. C., 2014. Electronic stability control for electric vehicle with four in-wheel motors. International Journal of Automotive Technology, 15 (4), p. 573−580.
[11]
Xiong, L. & Yu, Z., 2011. Vehicle Dynamic Control of 4 In-Wheel-Motor Drived Electric Vehicle. In: Electric Vehicles - Modelling and Simulations. s.l.: In Tech, pp. 67-107.
[12]
Ko, S. Y. et al., 2013. A Study on In-wheel Motor Control to Improve Vehicle Stability Using Human-in-the-Loop Simulation. Journal of Power Electronics, 13 (4), pp. pp. 536-545.
[13]
Morsy, E. M., 2005. The Effect of Using Intelligent Control Systems on The Dynamics Behavior of Electric Vehicles. Cairo: Helwan University.
[14]
Rajamani, R., 2006. Vehicle Dynamics and control. 1st ed. New York: Springer Science + Business Media Inc..
[15]
Geng, C., Mostefai, L., Denaï, M. & Hori, Y., 2009. Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer. IEEE Transactions on Industrial Electronics, 56 (5), pp. 1411 - 1419.
[16]
Jazar, R. N., 2008. Vehicle Dynamics (Theory and Application). 1st ed. New York: Springer Science + Business Media Inc.
[17]
LIAN, Y. F., ZHAO, Y., HU, L. L. & TIAN, Y. T., 2015. Cornering Stiffness and Sideslip Angle Estimation Based on Simplified Lateral Dynamic Models for Four-In-Wheel-Motor-Driven Electric Vehicles with Lateral Tire Force Information. International Journal of Automotive Technology, 16 (4), p. 669–683.
[18]
Burns, R. S., 2001. Advanced Control Engineering. 1st ed. Oxford: Butterworth-Heinemann.
[19]
Ogata, K., 2010. Modern Control Engineering. 5th ed. Upper Saddle River: Prentice Hall.
[20]
Lazarević, M. P., Batalov, S. A. & Latinović, T. S., 2013. Fractional PID Controller Tuned by Genetic Algorithms for a Three DOF`s Robot System Driven by DC motors. Grenoble, 2013 IFAC Joint Conference SSSC, FDA, TDS, pp. 385-390.
