978-981-99-6411-6.pdf

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 fo...

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Γλώσσα:English
Έκδοση: Springer Nature 2023
Διαθέσιμο Online:https://link.springer.com/978-981-99-6411-6
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spelling oapen-20.500.12657-861462023-12-13T11:33:01Z Annual Report on the Big Data of New Energy Vehicle in China (2022) Wang, Zhenpo 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) bic Book Industry Communication::T Technology, engineering, agriculture::TR Transport technology & trades::TRC Automotive technology & trades bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBT Probability & statistics 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. 2023-12-13T10:36:55Z 2023-12-13T10:36:55Z 2024 book ONIX_20231213_9789819964116_38 9789819964116 9789819964109 https://library.oapen.org/handle/20.500.12657/86146 eng application/pdf n/a 978-981-99-6411-6.pdf https://link.springer.com/978-981-99-6411-6 Springer Nature Springer Nature Singapore 10.1007/978-981-99-6411-6 10.1007/978-981-99-6411-6 6c6992af-b843-4f46-859c-f6e9998e40d5 014d0450-58a4-4cb4-b758-41e79e5e4b94 9789819964116 9789819964109 Springer Nature Singapore 335 Singapore [...] open access
institution OAPEN
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language English
description 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.
title 978-981-99-6411-6.pdf
spellingShingle 978-981-99-6411-6.pdf
title_short 978-981-99-6411-6.pdf
title_full 978-981-99-6411-6.pdf
title_fullStr 978-981-99-6411-6.pdf
title_full_unstemmed 978-981-99-6411-6.pdf
title_sort 978-981-99-6411-6.pdf
publisher Springer Nature
publishDate 2023
url https://link.springer.com/978-981-99-6411-6
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