基于观测器的发动机转矩跟踪模型预测控制

针对如何实现发动机转矩快速精准地跟踪期望转矩的问题,提出一种基于观测器的模型预测控制策略.首先,利用均值模型对汽油发动机的进气歧管压力动态、转矩和转速动态进行建模,考虑到发动机真实转矩不可测的情况,采用Lyapunov稳定性理论和可测转速信号设计观测器对进气歧管压力进行在线估计,进而获得发动机的实时估计转矩;然后,利用基于观测器的模型预测控制算法设计转矩跟踪控制器,通过C/GMRES数值优化算法在线求解滚动时域优化问题,实现转矩的实时跟踪控制;最后,利用汽油发动机实验台进行实验验证以表明所提出算法的有效性.

Observer based model predictive torque tracking control for gasoline engines

This paper proposes an observer based model predictive control for the torque tracking problem of automotive engines. The mean-value model involving the intake manifold pressure dynamics, torque production and rotational dynamics are built for characterizing the engine dynamic behaviors. Regarding the real torque is unmeasurable, an observer is designed based on Lyapunov stability analysis and the measured speed signal to online estimate the intake manifold pressure, and then the engine torque is calculated based on the estimated manifold pressure and the engine speed. The torque tracking controller is designed with the model predictive control scheme and the receding horizon optimization problem is solved by means of the numerical computation algorithm of C/GMRES. Finally, the experiment is performed on the full-scale gasoline engine test bench, and the results show the effectiveness of the proposed method.