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An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.

Hybrid powertrain has been proven to be an effective fuel-saving technology in commercial vehicles, but many hybrid commercial vehicles still use conventional diesel engines, resulting in limited fuel savings. The main purpose of this study is to enhance the thermal efficiency of a dedicated hybrid diesel engine focusing on the characteristic operating conditions. Via fundamental thermodynamics process analysis of internal combustion engine, steel piston with high compression ratio, air system involving two-stage turbocharger(2TC) with an intercooler, and late intake valve closing(IVC) timing are proposed to improve the thermal efficiency of the engine. Experimental results show that high compression ratio and lower thermal conductivity of the combustion chamber surface lead to lower heat release rates, requiring optimization of piston profile to accelerate the mixing rate. Besides, high compression ratio also leads to higher mechanical losses.

P2 hybrid electric vehicle is the single-motor parallel configuration integrating with an engine disconnect clutch (EDC) between the engine and the motor. The key point with P2 hybrid electric vehicle is to start the engine utilizing the single driving motor while still propelling the vehicle, which requires an appropriate engine-start control strategy and a high mechanical performance of EDC. Since the space for EDC is limited, EDC torque response is difficult to follow the torque command, which complicates the issue of precisely controlling the clutch. Consequently, methods proposed in massive papers are inappropriate for current EDC of target vehicle. Considering that slip control of shifting clutch also contributes to reducing impact of engine start assisted by EDC, a detailed engine-start control strategy was proposed to simplify the control of EDC for being applied to actual target vehicle.

The absence of combustion information continues to be one of the key obstacles to the intelligent development of engines. Currently, the cost of integrating cylinder pressure sensors remains too high, prompting attention to methods for extracting combustion information from existing sensing data. Mean-value combustion models for engines are unable to capture changes of combustion parameters. Furthermore, the methods of reconstructing combustion information using sensor signals mainly depend on the working state of the sensors, and the reliability of reconstructed values is directly influenced by sensor malfunctions. Due to the concentration of operating conditions of hybrid vehicles, the reliability of priori calibration map has increased. Therefore, a combustion information reconstruction method based on priori calibration information and the fused feature deviations of existing sensing signals is proposed and named the "Deviation-based Centroid Displacement Method" (DCDM).