Research on the Prediction of Dual Credit Situation of Passenger Car Enterprises Based on Multiple Factors

Abstract

Currently, China's new energy vehicle industry has entered a new stage of rapid development on a large scale. In order to ensure the advancement and innovation of the "Dual Credit Policy", the key assessment indicators such as the requirement ratio of NEV credits are in an urgent need to be made stricter. The strictness of the key assessment indicators is closely related to the development of China's energy-saving and new energy vehicle industry. However, currently, there is still a lack of systematic prediction methods for the mediumand long-term dual credit situation of passenger car enterprises in China. In this paper, a database for the prediction of the dual credit situation of passenger car enterprises is constructed using a combined "top-down" and "bottom-up" approach. Specifically, the NEV penetration rate in the industry is quantitatively evaluated using a multivariate regression model under the assumption of a discrete choice model, with the consideration of constraints such as resource endowment, charging infrastructure, and transformation costs of enterprises. The potential for fuel consumption reduction in conventional energy passenger cars of enterprises is determined using an optimal energy-saving technology choice model, which provides the annual decline in fuel consumption for enterprises. The calculation of the credits for NEV models and energy consumption is estimated using the rules of policy development and a simple conversion method. In order to make the prediction database more applicable to the real-world scenarios, it is also embedded with out-of-cycle energy-saving technologies, and research advancements in the latest policies and standards. This prediction database will greatly support the evaluation of the effectiveness of the "Dual Credit Policy" in the medium and long run, and assist enterprises in formulating credit compliance strategies.