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Nonlinear model predictive control of a GDI engine

机译:GDI引擎的非线性模型预测控制

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摘要

A model predictive approach to the control of a GDI engine is presented. Fuzzy Takagi-Sugeno type models are used to predict the future engine behaviour. The optimization algorithm is based on instantaneous linearization of the nonlinear prediction model at the current operating point. Special mode switching strategies are designed to minimize the torque bumps during combustion mode changes. The performance of the controller has been evaluated on the European driving cycle using a dynamic simulation model, including powertrain, chassis and driver's submodels. Results have been achieved that show the applicability of the approach to the control of GDI engines.
机译:提出了一种模型预测方法来控制GDI引擎。模糊的Takagi-Sugeno类型模型用于预测未来的发动机性能。优化算法基于当前工作点的非线性预测模型的瞬时线性化。特殊模式切换策略旨在最大程度地减少燃烧模式更改期间的扭矩冲击。控制器的性能已在欧洲驾驶循环中使用动态仿真模型进行了评估,其中包括动力总成,底盘和驾驶员的子模型。已经获得的结果表明该方法在GDI发动机控制中的适用性。

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