A novel approach to suspension control in electric vehicles with in-wheel motors: Finite horizon stochastic LQR with NSGA-II algorithm optimization
Abstract
A robust suspension-control strategy is presented for electric vehicles equipped with in-wheel motors and dynamic vibration absorbers (DVAs). A quarter-car model incorporating an in-wheel motor and an adjustable DVA is developed to mitigate excess unsprung mass. A finite-horizon stochastic linear quadratic regulator (FHS-LQR) that explicitly accounts for control delays and parameter uncertainties is coupled with an NSGA-II multi-objective optimizer to tune both DVA mechanics and controller weights. Compared with passive and conventional LQR baselines, the proposed framework reduces the root-mean-square values of sprung-mass acceleration, suspension deflection, tire dynamic load, and motor dynamic force by up to 40% under ISO 8608 road profiles and maintains performance for input delays up to 100 ms, demonstrating real-time feasibility and improved ride comfort.
Fields of Study & Subjects
Vibration Control and Rheological Fluids
Vehicle Dynamics and Control Systems
Effects of Vibration on Health
Publication details
- Journal / source
- Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
- Publisher
- SAGE Publications
- Volume
- 240
- Issue
- 10-11
- Pages
- 6964–6981
- Publication date
- 5 January 2026
- Language
- EN