Adaptive Control of the Heating System for Optimized Energy Consumption in Electric Vehicles

The heating system, the second largest energy consumer after the power train in electric vehicles (EV), has a significant impact on the overall energy management. We propose an optimized control algorithm for minimizing the energy consumption of the heating system for the passenger cabin. The presented adaptive control strategy combining a learning algorithm and dynamic programming optimizes the amount of energy consumption under consideration of the thermal comfort of EV passengers. Experiments shows that a reduction of energy consumption up to 12 % is achieved without sacrificing the preferred comfort.