Construction of SCR cheating models for in-use heavy-duty vehicles based on remote OBD data

Xiaowen Zhang; Quanshun Yu; Luowei Zhang; Zhicheng Ma; Lihui Wang; Fan Yang; Le Liu; Yuwei Wang

doi:10.1117/12.3010774

1 December 2023 Construction of SCR cheating models for in-use heavy-duty vehicles based on remote OBD data

Xiaowen Zhang, Quanshun Yu, Luowei Zhang, Zhicheng Ma, Lihui Wang, Fan Yang, Le Liu, Yuwei Wang

Proceedings Volume 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023); 129400B (2023) https://doi.org/10.1117/12.3010774
Event: Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 2023, Sipsongpanna, China

Abstract

The trend of China's automobile policy control is changing to ex-post supervision, and the emission control of in-use vehicles is gradually emphasised. In order to address the common SCR (Selective Catalytic Reduction) cheating technology in the market, this paper uses cheating and normal OBD (On-Board Diagnosis) data collection with different engine models as data sources, and develops three kinds of vehicle SCR cheating models based on OBD data using BP neural network, logistic regression and support vector machine, respectively, and verifies the accuracy. It was found that the support vector machine model is suitable as a test model due to its high accuracy, high generalisation performance, and simple and fast computation.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaowen Zhang, Quanshun Yu, Luowei Zhang, Zhicheng Ma, Lihui Wang, Fan Yang, Le Liu, and Yuwei Wang "Construction of SCR cheating models for in-use heavy-duty vehicles based on remote OBD data", Proc. SPIE 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 129400B (1 December 2023); https://doi.org/10.1117/12.3010774

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