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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Optimal Control of Diesel Engines: Numerical Methods, Applications, and Experimental Validation
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Optimal Control of Diesel Engines: Numerical Methods, Applications, and Experimental Validation

机译:柴油机的最优控制:数值方法,应用和实验验证

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In response to the increasingly stringent emission regulations and a demand for ever lower fuel consumption, diesel engines havebecome complex systems. The exploitation of any leftover potential during transient operation is crucial. However, even an experienced calibration engineer cannot conceive all the dynamic cross couplings between the many actuators. Therefore, a highly iterative procedure is required to obtain a single engine calibration, which in turn causes a high demand for test-bench time. Physics-based mathematical models and a dynamic optimisation are the tools to alleviate this dilemma. This paper presents the methods required to implement such an approach. The optimisation-oriented modelling of diesel engines is summarised, and the numerical methods required to solve the corresponding large-scale optimal control problems are presented. The resulting optimal control input trajectories over long driving profiles are shown to provide enough information to allow conclusions to be drawn for causal control strategies. Ways of utilising this data are illustrated, which indicate that a fully automated dynamic calibration of the engine control unit is conceivable. An experimental validation demonstrates the meaningfulness of these results. The measurement results show that the optimisation predicts the reduction of the fuel consumption and the cumulative pollutant emissions with a relative error of around 10% on highly transient driving cycles.
机译:为了响应日益严格的排放法规和对越来越低的燃料消耗的需求,柴油发动机已经成为复杂的系统。在瞬态运行期间,任何剩余电势的开发都是至关重要的。但是,即使是经验丰富的校准工程师也无法想到许多执行器之间的所有动态交叉联轴器。因此,需要高度迭代的过程来获得单个发动机校准,这又导致对测试台时间的高要求。基于物理的数学模型和动态优化是缓解这一难题的工具。本文介绍了实现这种方法所需的方法。总结了面向优化的柴油机建模,并提出了解决相应的大规模最优控制问题所需的数值方法。所显示的在长行驶曲线上的最优控制输入轨迹可提供足够的信息,以便得出因果控制策略的结论。示出了利用该数据的方式,其表明可以想到发动机控制单元的全自动动态校准。实验验证证明了这些结果的意义。测量结果表明,该优化可预测燃油消耗的减少和污染物累积排放量,在高瞬态驾驶循环中的相对误差约为10%。

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