YU Yuewei, LI Bo, ZHAO Leilei, et al. Optimal Control of Active Suspension for In-Wheel-Motor-Driven Electric Vehicles Integrating Analytical Calculation[J]. Journal of Xi'an Jiaotong University, 2026, 60(8): 229-239.
DOI:
YU Yuewei, LI Bo, ZHAO Leilei, et al. Optimal Control of Active Suspension for In-Wheel-Motor-Driven Electric Vehicles Integrating Analytical Calculation[J]. Journal of Xi'an Jiaotong University, 2026, 60(8): 229-239.DOI: 10.7652/xjtuxb202608020.
Optimal Control of Active Suspension for In-Wheel-Motor-Driven Electric Vehicles Integrating Analytical Calculation
To address the problems of low real-time solution efficiency of control performance evaluation indicators and difficulty in adaptive adjustment of control weighting coefficients for the optimal control of active suspensions in in-wheel-motor-driven electric vehicles (IWMD-EVs)
an optimal control weighting coefficient design method based on analytical calculation was proposed. First
based on a three-degree-of-freedom active suspension model of IWMD-EVs
the analytical formulas for the root mean square (RMS) values of the vehicle body vertical acceleration
suspension dynamic stroke
and tire dynamic displacement for optimal control-based IWMD-EV active suspension systems were derived using random vibration theory and the residue theorem integral solution method. Then
from a theoretical analysis perspective
the complex
problem of solving the control weighting coefficients was transformed into a problem of solving the same-scale quantization coefficients and the performance evaluation weighting coefficients. An adaptive adjustment method for optimal control weighting coefficients of IWMD-EV active suspension systems based on analytical calculation was established
by which rapid dynamic adjustment of control weighting coefficients is realized with changes in vehicle driving conditions. Finally
the reliability of the established method was verified through bench tests. The results show that the maximum deviation between analytical calculation results and experimental test results is within 8%
indicating that the established RMS analytical formulas are correct and reliable; compared with traditional linear quadratic Gaussian control and
H
∞
control methods
the proposed method significantly improves the ride comfort of IWMD-EVs under different driving conditions. This study provides a new approach for the design of optimal control-based IWMD-EV active suspension systems.
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