Abstract The engine performances and emissions of light-duty diesel engines in plateau regions have attracted more attention due to the upcoming China VI emission regulations for light-duty vehicles. In order to obtain a superior performance for a diesel engine running at high altitude, in this research, multi-objective optimization was conducted in an entire operating region for a light-duty diesel engine operating at an altitude of 1960 m. A support vector machine (SVM) was employed to set up a surrogate model between the calibration parameters and the engine performance parameters. The multi-objective optimization of the fuel consumption and the emissions was carried out using a genetic algorithm with the premise of keeping the same power performance of the original engine within durability constraints and with a minimum smoke limit. The results showed that the SVM regression model had excellent predictive performance and generalization abilities, and that the model could accurately predict the various performance parameters of the diesel engine. The diesel engine running in the plateau region could achieve a good comprehensive performance with the proposed multi-objective optimization method. In comparison with the base engine in the plateau region, a simultaneous reduction of 52.92% for the brake specific NOx emission and 0.67% for the brake specific fuel consumption was achieved, with an acceptable increase of smoke emission.

中文翻译：

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基于支持向量机和遗传算法的高空轻型柴油机建模与优化

摘要 随着轻型车国六排放法规的出台，高原地区轻型柴油机的发动机性能和排放问题备受关注。为了使柴油机在高空运行时获得优越的性能，本研究对1960 m高空运行的轻型柴油机进行了整个运行区域的多目标优化。采用支持向量机（SVM）在标定参数和发动机性能参数之间建立代理模型。油耗和排放的多目标优化采用遗传算法进行，前提是在耐久性约束和最小烟雾限制下保持原发动机相同的动力性能。结果表明，SVM回归模型具有优良的预测性能和泛化能力，该模型能够准确预测柴油机的各种性能参数。采用所提出的多目标优化方法，在高原地区运行的柴油机可以获得良好的综合性能。与高原地区基础发动机相比，制动比NOx排放同时降低52.92%，制动比油耗降低0.67%，烟气排放量增加尚可。采用所提出的多目标优化方法，在高原地区运行的柴油机可以获得良好的综合性能。与高原地区基础发动机相比，制动比NOx排放同时降低52.92%，制动比油耗降低0.67%，烟气排放量增加尚可。采用所提出的多目标优化方法，在高原地区运行的柴油机可以获得良好的综合性能。与高原地区基础发动机相比，制动比NOx排放同时降低52.92%，制动比油耗降低0.67%，烟气排放量增加尚可。