A novel multiobjective optimal LQ control strategy for energy harvesting in vehicle suspension systems

A novel optimal LQR state-feedback control law is proposed for energy harvesting maximization in regenerative suspension systems where an actively governed electromechanical actuator is used in place of the viscous damper. A special LQR cost function is considered that directly maximizes the electrical power generated by the electromechanical actuator. Other conflicting control objectives, such as ride comfort and road handling, may be considered along with the energy harvesting objective in the proposed control setup, allowing one to directly trade-off among them depending on the application. Specifically, as an example, a condition for trading-off between energy harvesting and ride comfort is added to the optimization problem via forcing a bound on the so called Ride Index. The proposed control law is finally contrasted with the Regenerative damper and MIPC H₂ control strategies usually considered in the literature for energy harvesting applications and it is compared in simulative studies via MATLAB/Simulink on a quarter-car model and the CarSim Simulator. In particular, as shown in the results, it is highlighted that the proposed control law yields an increase in harvested energy of 37.3 % and 27.8 % compared to the Regenerative Damper and MIPC H₂ strategies, respectively. Beyond its performance benefits, the LQR-based approach offers a streamlined implementation process, requiring only two tuning parameters to meet the Ride Index constraint, significantly fewer than the four parameters needed by MIPC H₂, which include one for energy optimization and three for signal filtering. Additionally, the proposed method entails lower computational overhead, making it well-suited for real-time applications.