Improved MPC energy management for series hybrid electric vehicles based on dynamic equivalent fuel consumption

In this paper, the energy management control for series hybrid electric vehicles is carried out. The control method is model predictive control, and rolling optimization method is dynamic programming. Firstly, mathematical modeling of energy management of series hybrid vehicle was conducted on, clarifying the components involved in energy management. Then the model predictive control and dynamic programming are introduced. The concepts of dynamic equivalent fuel consumption and SOC correction term are introduced into the cost function of dynamic programming, and the new method is called the model predictive control method based on dynamic equivalent fuel consumption. The dynamic equivalent fuel consumption is reflected in the refinement of the fuel equivalent factor model, allowing the customized fuel equivalent factor to change according to the current driving conditions, thereby making the equivalent fuel consumption cost more accurate. On this basis, a PI controller is introduced to dynamically change the fuel equivalent factor, making the SOC value close to the ideal SOC value; At the same time, SOC correction is introduced into the cost function of dynamic programming, so that the SOC value can quickly approach the reference SOC value. Through simulation verification, it was found that the new method has better control effects on battery SOC and vehicle equivalent fuel consumption compared to three scenarios: rule-based management control, traditional model predictive energy management control, and dynamic equivalent fuel consumption model predictive energy management control. On series hybrid vehicles, the improved MPC energy management method based on dynamic equivalent fuel consumption is obviously more effective.