Active Vehicle Suspension Control Strategy Based On a Road Recognition Algorithm

Electrified automotive suspension systems are advancing rapidly due to improvements in hardware and software, essential for both comfort and performance. While initially limited to high-end vehicles, these systems are now more accessible due to reduced production costs. However, market products still lag behind academic research, highlighting the need for cost-effective and energy-efficient solutions. This study focuses on an active hydraulic suspension system, developing control strategies to optimize performance while minimizing energy consumption, using Matlab, Simulink, and Simscape simulations. The system utilizes an innovative rotary valve prototype developed at Polytechnic of Turin, Italy, which modulates actuator force by adjusting flow rates and pressure drops. A road recognition algorithm using an augmented Kalman filter reconstructs the road profile and vertical velocity, enabling a two-level adaptive control system for actuator force and rail pressure. The system shows improved vertical acceleration behavior when the control strategy is set in a comfort-oriented mode, reducing its RMS value by 24.14%, without compromising vehicle handling when set in a sport-oriented mode. Simulations also suggest that optimizing rail pressure regulation could enhance energy efficiency. While promising, the algorithm's real-world performance may differ due to road and environmental complexities. The study offers new contributions, including the rotary valve design and the advanced road recognition algorithm, proposing an energy-efficient control system that could lead to cost-effective, high-performance suspension solutions for real-world applications.