摘要
如何控制汽油车污染物排放水平,是汽车产业亟待解决的问题。随着电子控制技术的日趋成熟,电控单元可以实现更加复杂的控制和算法,通过基于模型的控制技术解决排放问题也成为了汽车控制领域的研究热点。本文从汽油机排放优化标定技术的基本原理与流程入手,研究了基于模型的排放控制技术的发展优势及应用现状,总结出基于机器学习算法的发动机排放性能建模是提升排放标定水平的重要技术手段,并有较大研究潜力。
How to control the pollutant emission level of gasoline vehicles is an urgent problem to be solved in the automobile industry.With the maturity of electronic control technology,the electronic control unit can realize more complex control and algorithms,and solving the emission problem through model-based control technology has also become a research hotspot in the field of automotive control.This paper starts with the basic principle and process of gasoline engine emission optimization calibration technology,studies the development advantages and application status of model-based emission control technology,and concludes that engine emission performance modeling based on machine learning algorithm is an important technical means to improve the level of emission calibration,and has great research potential.
作者
戴超麒
刘炜
谷鑫
李东明
张成
Dai Chaoqi;Liu Wei;Gu Xin;Li Dongming;Zhang Cheng
出处
《时代汽车》
2022年第13期22-24,共3页
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关键词
排放
标定
模型
机器学习
emissions
calibration
model
machine learning