A Heuristic Supervisory Controller for a 48V Hybrid Electric Vehicle Considering Fuel Economy and Battery Aging

Most studies on supervisory controllers of hybrid electric vehicles consider only fuel economy in the objective function. Taking into consideration the importance of the energy storage system health and its impact on the vehicle’s functionality, cost, and warranty, recent studies have included battery degradation as the second objective function by proposing different energy management strategies and battery life estimation methods. In this paper, a rule-based supervisory controller is proposed that splits the torque demand based not only on fuel consumption, but also on the battery capacity fade using the concept of severity factor. For this aim, the severity factor is calculated at each time step of a driving cycle using a look-up table with three different inputs including c-rate, working temperature, and state of charge of the battery. The capacity loss of the battery is then calculated using a semi-empirical capacity fade model. Eventually, the fuel economy, and capacity loss as two of the most important objectives are compared with and without implementing the proposed controller. In the comparative study, four customized driving cycles are considered, including calm/aggressive drivers and low/high vehicle speeds. The results suggest improvement in the objectives and trade-off between fuel economy and battery aging. The proposed heuristic controller can be implemented in different types of hybrid electric vehicles.