Real-time controller design for a parallel hybrid electric vehicle using neuro-dynamic programming method

The use of the neuro-dynamic programming method for real-time control of a parallel hybrid electric vehicle is addressed in this study. The validated model of a research prototype parallel hybrid electric light commercial vehicle, FOHEV I, is used in the numerical parts of this paper. A diesel engine and an electric motor power the front and rear axles, respectively. Due to the computational complexity and resulting burden for optimum power distribution in the hybrid electric powertrain, real-time computation using dynamic programming is not feasible. Sub-optimal optimization techniques are available for pre-defined speed profiles, however, the vehicle speed profile depends on the driver input and vehicle and road conditions and is not known a priori. A neuro-dynamic programming method is proposed here to solve this problem. The results are compared with and found to be quite close to the optimal ones computed using dynamic programming.