A Comparative Analysis of Optimization Strategies for a Power-Split Powertrain Hybrid Electric Vehicle

In this paper, two strategies based on the use of roadway traffic prediction data to optimize the energy consumption of Hybrid Electric Vehicles are compared. For both strategies, predictive traffic data is sent to the supervisory controller in order to adjust the Equivalent Consumption Minimization Strategy (ECMS). In the first approach, the predicted driving profile is divided into time horizons of equal length and the optimal control input is calculated for each of them. In the second approach, the control input is periodically recalculated, thus, adapting to changes in the predicted driving profile. While both strategies reduced energy consumption, the second approach showed its superiority with a maximum improvement of 6.85 %.