Methods from optimal control theory have been used since the past decade to design model-based energy management strategies for hybrid electric vehicles (HEVs). These strategies are usually designed as solutions to a finite-time horizon, constrained optimal control problem that guarantees optimality upon perfect knowledge of the driving cycle. Properly adapted these strategies can be used for real-time implementation (without knowledge of the future driving mission) at the cost of either high (sometime prohibitive) computational burden or high memory requirement to store high-dimensional off-line generated look-up tables. These issues have motivated the research reported in this chapter. We propose to address the optimal energy management problem over an infinite time horizon by formulating the problem as a nonlinear, nonquadratic optimization problem. An analytical supervisory controller is designed that ensures stability, optimality with respect to fuel consumption, ease of implementation in real-time application, fast execution and low control parameter sensitivity. The approach generates a drive cycle independent control law without requiring discounted cost or shortest path stochastic dynamic programming introduced in the prior literature.


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    Title :

    Model-Based Optimal Energy Management Strategies for Hybrid Electric Vehicles


    Contributors:


    Publication date :

    2014


    Size :

    20 Seiten





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Print


    Language :

    English




    Energy management strategies for hybrid electric vehicles

    Ambuehl,D. / Swiss Federal Inst.of Technol.,ETH,CH | Automotive engineering | 2009