Control management system for incorporating hydraulic power into hybrid electric vehicles

Hybrid electric vehicles, which combine a combustion engine with an electric motor, serve as a bridge between conventional gas-powered vehicles and battery electric vehicles. Incorporating hydraulic power systems into these vehicles alongside electric power systems can increase power density and energy recovery in a smaller and more flexible design, boosting performance.

However, switching between electric and hydraulic power systems can be complicated and, if not handled correctly, can result in an unpleasant and inefficient drive. Guan et al. developed a control management system to manage these transitions more effectively.

“[Power mode switching] can cause sudden shocks due to differences in response times between the electric motor and hydraulic pump/motor,” said author Qiqiang Guan. “These shocks not only disrupt vehicle stability and comfort but also lead to inefficiencies in energy use.”

The team created a control management system that employs the Soft Actor-Critic (SAC) reinforcement learning algorithm, trained using a multi-condition model that covers a range of operating scenarios. They tested the resulting control system in a real-world drive through urban and highway environments, where it outperformed a less sophisticated, rule-based control system in both energy efficiency and ride smoothness.

The researchers are looking to improve the algorithm by making it more flexible and versatile.

“Moving forward, I plan to further optimize the SAC algorithm by integrating more complex driving scenarios and improving its real-time control capabilities,” said Guan. “We are also exploring ways to refine the system for broader vehicle applications, focusing on enhancing its adaptability to different hybrid vehicle architectures and real-world driving conditions.”

Source: “Optimization of longitudinal impact during mode switching of electro-hydraulic hybrid vehicles based on soft actor-critic algorithm,” by Qiqiang Guan, Hongxin Zhang, Jian Yang, and Jie Zhou, Journal of Renewable and Sustainable Energy (2025). The article can be accessed at https://doi.org/10.1063/5.0287266 .