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    • Research on Nox Emissions Prediction Model for Heavy Duty Diesel Vehicles
    DOI：10.13949/j.cnki.nrjgc.2019.06.002
    Key Words:NOx emissions  portable emissions measurement system  adaptive learning rate method  emissions prediction
    Author NameAffiliation
    WANG Zhihong,YUAN Yu,WANG Shaobo,WU Penghui,YAN Hao,HU Jie 1.Hubei Key Laboratory of Advanced Technology for Automotive Components(Wuhan University of Technology), Wuhan 430070, China； 2.Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan 430070, China 
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    Abstract:Based on the portable emissions measurement system(PEMS), an actual road emissions test was performed on a certain type of heavy-duty diesel vehicle, and NOx emissions were fitted by the vehicle specific power(VSP) and vehicle traction force(VA) respectively. Using these two factors VSP and VA as input parameters, a double-hierarchical BP neural network improved by adaptive learning rate method was used to train and predict the NOx emissions. Compared with the original BP network prediction, the Pearson correlation coefficient between a predicted value and an actual value was increased by 0.1136, and the relative error was reduced by 0.6621%. The accuracy of the improved neural network prediction was promoted, and the generalization ability was strong. The improved neural network is applicable for the real-time prediction of the NOx emissions of this heavy-duty diesel vehicle, which has certain engineering application value.
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