Research on Dynamic Coordination Active Mode Switching Control Strategy for Hybrid Electric Vehicle Based on Traffic Information

In traditional hybrid-vehicle mode switching, a switch when it changes in road conditions is sensed. Because of the delays in the control system, lags in switching and large impacts on the switching process occur, in what is referred to as "passive mode switching.'' Via a combination of an intelligent networked hybrid vehicle with environmental sensing, "passive mode switching'' can be converted into "active mode switching,'' reducing the impact degree during the switching process and increasing ride comfort. Combined with the application of intelligent transportation system in current traffic, an intelligent traffic scene with optimal traffic-light control (OTLC) is established. The OTLC algorithm determines the future driving-state information of the hybrid vehicle in a built scenario and predicts the driving mode of the hybrid vehicle for the next moment. The current mode and future mode are compared, active control of key components, such as the engine, motor, clutch, and electric-mechanical continuously variable transmission (EMCVT), under the premise of different conditions, is made possible, and corresponding dynamic coordinate active-mode-switching control strategies are developed. The proposed control strategy is simulated and verified on a built-in hardware-in-the-loop (HIL) test platform based on traffic scenarios. The results show that the dynamic coordinated active-mode-switching control strategy presented in this paper is superior to the traditional mode-switching control strategy and that it can overcome the problem of switching lag due to delays in the control system and the large impact during the switching process, reducing the impact degree by about 21.2%, which improves ride comfort.