Real-time optimal control of plug-in hybrid vehicles with trip preview

The global optimal solutions of energy management of hybrid electric vehicles depend on future driving conditions. This paper investigates a potential real-time methodology to integrate long-horizon preview information for plugin hybrid vehicles. Equivalent Fuel Consumption Minimization Strategy (ECMS) is deployed as an instantaneous real-time minimization strategy with parameters adjusted by estimated future driving conditions and obtained either from Dynamic Programming (DP) or from a global ECMS. The preview information is decomposed into future road terrain stored as invehicle 3D maps and future velocity estimated from streaming or historic traffic data. We show that with estimated future information, substantial reduction in fuel use, up to 13% is possible compared with a rule-based control strategy without any preview. Further improvement of fuel consumption on the order of 1% could be achieved with exact future information.