Loss optimization and ultracapacitor pack sizing for vehicles with battery/ultracapacitor hybrid energy storage

Battery and ultracapacitor hybrid energy storage systems have long been proposed as alternatives to battery-only systems for electrified vehicles. Prior research has focused on system topologies, dc/dc converter design, control methods, and evaluating specific applications. This work utilizes a rule-based control method and dynamic programming combined with a vehicle model to evaluate the reduction in energy storage losses that can be achieved for various drive cycles and ultracapacitor pack sizes. Dynamic programming is used to determine the optimum power split between the battery and ultracapacitor pack for a specified drive cycle and calculates the best performance a causal control algorithm could achieve. The analysis shows that dynamic programming can significantly improve the loss reductions compared to the basic rule-based control, making it possible to reduce the size of the ultracapacitor pack needed to deliver meaningful energy savings. Experimental tests have been carried out on battery and ultracapacitor cells that raise confidence in the accuracy of the model predictions for drive cycle metrics.