Control Strategy for Electric Startup of P2.5-PHEV Based on Slope Memory and Driver’s Startup Intention

Abstract

P2.5 plug-in hybrid electric vehicles (P2.5-PHEVs) exhibit high transmission efficiencies and no power interruption in the shifting and mode switching process; thus, they have broad application prospects. The power transmission in a PHEV under pure electric startup does not entail the clutch, and the initial torque of the motor is often set under the condition that the maximum allowable slope should not lead to backward sliding, which leads to the problems of excessive jerk in small-slope startup and catapulting when startup occurs downhill. The optimal method is to set different initial torques according to different gradients; however, the vehicle would still be in the pre-startup stage, making it impossible to estimate the slope using a dynamic method. In view of the foregoing problems, according to an analysis of pure electric startup dynamics, a slope-memory-based strategy for estimating and storing the slope during the vehicle movement before parking is proposed. During startup, the initial torque is set according to the memorized slope. In the processes of startup and acceleration, the driver’s startup intention is identified, and different jerk control targets are set. The torque of the acceleration process is controlled according to the set initial torque and jerk target. Simulation results indicate that the maximum jerk of the proposed strategy is reduced by 23.6% for startup on a 5% ramp and by 57.5% for startup at 15% downhill; thus, the strategy mitigates the problems of the excessive jerk and catapult for startup on a small slope.

Keywords

• P2.5 hybrid powertrain configuration
• road slope estimation
• startup intention identification
• vehicle startup process