In this paper, an optimal gear shifting control strategy based on Dynamic Programming (DP) for a vehicle equipped with a Power-Shift Automated Manual Transmission (PS-AMT) is proposed in order to explore the potential fuel savings. Simulation results on the city part of the New European Drive Cycle (NEDC), called ECE cycle, reveal that the relative fuel economy improvement can be reached up to 15.4% by applying DP shifting strategy compared to the case of applying a prescribed gear shift schedule. A forward facing dynamic power train model and control system are designed and developed for the prototype PS-AMT vehicle in order to validate the system modeling and shifting algorithm implementation. The test results of the prototype vehicle on the roller bench show that 11.2% improvement of fuel economy is achieved. It can be concluded that significant potential fuel savings can be obtained by optimal gear shift control and the proposed design method is consistent.

Control strategies for Hybrid Electric Vehicles (HEVs) are generally aimed at optimally choosing the power distribution between the internal combustion engine and the electric motor in order to minimize the fuel consumption and/or emissions. Using vehicle navigation systems in combination with Global Positioning Systems and Geographical Information Systems allow further optimization of the power distribution by utilizing the route information. In this paper, a new control algorithm based on a combination of dynamic programming and classical optimal control theory is proposed for the Energy Management System in parallel HEVs to improve the fuel economy over a preview route segment. The proposed algorithm optimizes not only the gear position and the engine power yet also the vehicle velocity. The vehicle is controlled to complete this route segment in a predefined time length. Using this method more than 11% fuel saving is computed on an optimized cycle compared to a standard city cycle with equal time length and average speed.

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