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            Annual Report on the Big Data of New Energy Vehicle in China (2022)

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            Author(s)
            Wang, Zhenpo
            Language
            English
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            Abstract
            This is an Open Access book. This book based on static indicators and dynamic big data from local electric vehicles, is the first New-Energy Vehicles (NEVs) research report on the Big Data in China. Using the real-time big data collected by China's National Monitoring and Management Platform for NEVs, this book delves into the main annual technological progress of NEVs, the vehicle operating characteristics, it also anticipates the trend of NEVs industry. Various graphs & charts, detailed data this book offers will familiarize readers with the operation characteristics and practical application of China's NEVs industry and popularize the concept of automobile electrification. Besides, this book also makes an objective evaluation of the current situation and technological improvement of China's NEVs industry, presenting sensible suggestions for the development of the industry. This book is written for government staff, researchers, college staff, and technical staff of automobile and spare parts enterprises, which serves as an important reference for the decision-making of government departments and strategic decisions of automotive companies.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/180280
            Keywords
            New Energy Vehicles (NEVs); Electric Vehicle (EV); Big Data; NEVs Technology Improvement; Electric Vehicle Sales Promotion; Electric Vehicle Driving Characteristics; Electric Vehicle Charging Characteristics; Battery swapping; Plug-in Hybrid Electric Vehicle (PHEV); Fuel Cell Vehicle (FCV)
            DOI
            10.1007/978-981-99-6411-6
            ISBN
            9789819964116, 9789819964109
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Singapore, 2024
            Imprint
            Springer Nature Singapore
            Classification
            Automotive technology & trades
            Probability & statistics
            Pages
            335
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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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