Optimal energy management for a hybrid energy storage system for electric vehicles based on Stochastic Dynamic Programming

For electric and hybrid electric cars, commonly nickel-metal hydride and lithium-ion batteries are used as energy storage. The size of the battery depends not only on the driving range, but also on the power demands for accelerating and braking and life-time considerations. This becomes even more apparent with short driving ranges, e.g. in commuter traffic. By hybridization of the storage, adding double layer capacitors, the battery can be relieved from the stress of peak power and even downsized to the energy demands instead of power demands. The dimensioning of the storage is performed by a parametric study via Deterministic Dynamic Programming. To determine an energy management to control the power flows to the storage online during operation which considers the stochastic influences of traffic and the driver, Stochastic Dynamic Programming is investigated and compared to the optimal strategy found during the dimensioning.

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