Research on the Optimization of a Diesel Engine Parallel-Operation Speed Control Algorithm Based on Model Predictive Control

Aiming at the problems of large speed synchronization error and prominent speed overshoot existing in conventional PID control algorithms widely adopted for diesel-engine parallel-unit speed-governing systems, this paper proposes a speed control algorithm based on Model Predictive Control (MPC) for dual-diesel-engine parallel operation. A quasi-steady-state method is employed to establish the coupled state-space model for dual-engine parallel operation. Leveraging the prediction-optimization and multi-constraint regulation characteristics of MPC, the fuel-injection outputs of the two diesel engines are regulated respectively by two independent SISO MPC controllers, which share the identical speed reference and are coordinated at the logic level through the Stateflow engagement/disengagement state machine to achieve speed synchronization. Comparative simulations under different operating conditions are carried out on the Matlab/Simulink platform. The simulation results show that the proposed MPC algorithm can effectively suppress speed fluctuations between the two diesel engines under the tested operating conditions compared with the traditional PID control. Furthermore, a hardware-in-the-loop test platform is constructed for validation in the embedded environment. The test results reproduce all operating conditions of offline simulation, achieving zero speed overshoot and restricting the dual-engine synchronization deviation within ±3 rpm, which are consistent with the offline simulation results. The real-time computational capability and engineering feasibility of the proposed algorithm are therefore verified. The proposed method is applicable to stable speed-governing scenarios of marine dual-diesel-engine parallel-unit sets.