Development of model predictive charging control of in-vehicle batteries
for home energy management based on vehicle state prediction

The team lead by the research director Tatsuya Suzuki, Professor at Nagoya University reports a model predictive control strategy for charging control of in-vehicle batteries that minimizes the electricity fee at each household. The proposed control scheme exploited the predicted information on home power load and future vehicle state in the household. The prediction algorithm of future vehicle state was developed based on semi-Markov model and dynamic programming, in addition, it can be implemented in receding horizon manner, i.e., the predicted vehicle state is updated at every control cycle based on the new observation. Effectiveness of the proposed charging control was demonstrated by using an experimental testbed. As the result, the electricity fee at each household can be reduced by 10 to 40%.