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Hierarchical Optimization Decision-Making Method to Comply with China’s Fuel Consumption and New Energy Vehicle Credit Regulations

Author

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  • Kangda Chen

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

  • Fuquan Zhao

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

  • Han Hao

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China
    China Automotive Energy Research Center, Tsinghua University, Beijing 100084, China)

  • Zongwei Liu

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

  • Xinglong Liu

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    Tsinghua Automotive Strategy Research Institute, Tsinghua University, Beijing 100084, China)

Abstract

The national targets of reaching carbon peak in 2030 and carbon neutrality in 2060 propose higher requirements for energy conservation and emission reduction of China’s automobile industry. As an important measure for the government, the fuel consumption and new energy vehicle (NEV) credit policy system has a significant impact on the Chinese and even the global vehicle market. Considering the lack of a systematic evaluation model for China’s fuel consumption and NEV credit regulations, this study establishes a hierarchical optimization decision-making model based on technology frontier curves and a multi-dimension database containing extensive data of technologies, products, and enterprises in the Chinese market to simulate and evaluate the technology compliance and policy impact under multiple regulations. The results show that, from the perspective of the technology frontier curve, gasoline technologies still have great cost-effectiveness advantages when the fuel-saving requirement is less than 46%, and the space for plug-in hybrid electric vehicles (PHEVs) and range-extended electric vehicles (REVs) is gradually shrinking due to the cost reduction of battery electric vehicles (BEVs). BEV400 will be better than PHEV70 and REV100 when the fuel-saving requirement is higher than 79%. Diesel vehicles are always not competitive in the passenger car market. In terms of the compliance of corporate average fuel consumption (CAFC) regulation, the start-stop technology will be gradually phased out and mild hybrid electric vehicles will be rapidly introduced due to their high cost-effectiveness in 2025. With the tightening of regulations, the penetration rate of BEVs and PHEVs will be 23.7% and 6.7%, respectively, and mild hybrid electric vehicles will be gradually replaced by strong hybrid electric vehicles in 2030. By 2035, the penetration rate of BEVs and PHEVs will be 43.6% and 6% further. For the CAFC and NEV credit regulation (widely known as the dual credit regulation), the single-vehicle credit poses a greater impact on the penetration of NEVs than corporate credit percentage limitation and is the key factor that should be focused on. The NEV credit limitation in the dual credit regulation could push ‘poor performance’ automakers to produce the required number of NEVs and meet the bottom line. However, in the long term, when compared to the CAFC regulation, the dual credit regulation is more lenient, due to NEVs being able to get double benefits both on NEV credit and CAFC credit, and NEV credit can also unidirectionally compensate CAFC credit under the dual-credit policy context. With the increased penetration and cost reduction of NEVs, the ‘averaging’ effect of dual credit regulation will inhibit the development of energy-saving and new energy vehicles. Therefore, eliminating the connection between NEV credit and CAFC credit or only leaving the CAFC and the fuel consumption limit regulations in the future will be better for the long-term development of the energy-saving and new energy vehicle industry.

Suggested Citation

  • Kangda Chen & Fuquan Zhao & Han Hao & Zongwei Liu & Xinglong Liu, 2021. "Hierarchical Optimization Decision-Making Method to Comply with China’s Fuel Consumption and New Energy Vehicle Credit Regulations," Sustainability, MDPI, vol. 13(14), pages 1-25, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7842-:d:593756
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