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One of the most important challenges for effective energy management in Hybrid Electric Vehicles (HEVs) applications is the capability of correctly estimate the batteries State of Charge (SoC). This task is particularly arduous to accomplish in real-time, due to the complexity and nonlinearities, as well as the inevitable presence of on-board measurements errors. The objective of this paper is to develop a NiMH battery model which accounts for the relevant dynamics related to HEV applications. A detailed series of experiments allowed for system identification to be performed in order to design an equivalent electrical circuit model of the battery, where capacitors take care of voltage relaxations, while resistors model all forms of energy losses. Experimental results are then compared with model prediction, resulting in variances limited to less than 3.5%. Finally, the validated model was inverted to serve as a main component of a proposed SoC estimator, whose performance is of key relevance for effectiveness of HEVs. Results during actual vehicle operations are shown delineating a successful application.

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