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Combustion closed-loop control is now being studied intensively for engineering applications to improve fuel economy. Currently, combustion closed-loop feedback control is usually based on the cylinder pressure signal, which is the most direct and exact signal that reflects engine working process. Although there were some relatively cheap types of in-cylinder pressure sensors, cylinder pressure sensors have not been widely applied because of their high price now. Moreover, the combustion analysis based on cylinder pressure imposes high requirements on the information acquisition capability of the current ECU, such as high acquisition and analog-digital conversion frequency and so on. For developing a low price and feasible technology, a new engine information feedback method based on model calculation and crank angular velocity measurement was proposed. A simplified combustion model was operated in ECU for the real-time calculation of cylinder pressure and combustion parameters.

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).