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市場調查報告書

EV能源管理用AI:使用AI的EV電池的設計、製造、續航距離、導航最佳化、車隊管理、V2G (Vehicle to Grid) 用途的改善

AI for EV Energy Management: Using AI to Improve EV Battery Design, Manufacturing, Range, Navigation Optimization, Fleet Management, and Vehicle-to-Grid Applications

出版商 Guidehouse Insights (formerly Navigant Research) 商品編碼 967891
出版日期 內容資訊 英文 46 Pages; 38 Tables, Charts & Figures
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EV能源管理用AI:使用AI的EV電池的設計、製造、續航距離、導航最佳化、車隊管理、V2G (Vehicle to Grid) 用途的改善 AI for EV Energy Management: Using AI to Improve EV Battery Design, Manufacturing, Range, Navigation Optimization, Fleet Management, and Vehicle-to-Grid Applications
出版日期: 2020年10月26日內容資訊: 英文 46 Pages; 38 Tables, Charts & Figures
簡介

EV產業,為了提高EV體驗積極應用AI技術。Guidehouse Insights 預計由於冠狀病毒的大流行儘管造成銷售台數一時後退,今後10年全部的地區EV銷售將變得順利。AI技術的使用,強化EV的效率與機能,提高EV OEM的競爭力,預期在克服未來的EV購買者的疑慮上日益發揮重要作用。AI為了使EV生態系統更富有魅力且有競爭力,最終預計加速EV的採用。

本報告提供EV能源管理AI的相關調查,目前這一代EV硬體和服務中使用的內部OEM AI應用以及EV價值鏈中待定或計劃中的AI使用(第二代應用),還討論了第三代應用程式,這些應用程式有望進一步增強現有或計劃中的AI功能,從而為整體EV體驗做出貢獻,但尚未實現。除了這些內部OEM用例之外,本報告還概述了與EV相關的AI機會,涉及商業車隊管理,公用電網管理和EV充電整合。

目錄

第1章 摘要整理

  • 簡介
  • 市場預測

第2章 市場問題

  • 簡介
    • EV電力技術概要
    • 市場趨勢
    • 市場障礙
  • EV生態系統的AI為基礎的應用
    • 內部OEM應用
    • EV生態系統的第三方AI解決方案

第3章 主要企業

  • Auto Motive Power
  • Bidgely
  • C4V
  • Ford Motor Company
  • General Motors
  • Lucid Motors
  • Nissan Motor Corporation
  • Robert Bosch
  • Tesla
  • Texas Instruments
  • TomTom

第4章 市場預測

  • 簡介
  • 內部EV OEM應用提供預測:各EV出貨
    • 汽車AI應用的預測
  • 第三方EV AI解決方案的預測
    • EV車隊AI應用的預測
    • EV計劃的公共事業AI應用的預測
  • 結論、建議

第5章 縮寫、簡稱清單

第6章 圖表

第7章 調查範圍、調查來源、調查手法、註記

目錄
Product Code: MF-AIBM-20

EVs are viable substitutes for many vehicles that rely on internal combustion engines (ICEs). Although many EV drivers are enthusiastic about their vehicles, prospective customers have legitimate reasons for hesitating to make the switch. The EV industry is aware of these concerns and is aggressively applying AI technology to enhance the EV experience.

Despite a temporary setback in unit sales due to the coronavirus pandemic, Guidehouse Insights expects strong EV sales in all regions over the next decade. The use of AI technology is anticipated to play an increasingly important role in enhancing the efficiency and capabilities of EVs, advancing the competitive positioning of EV OEMs, and overcoming the objections of prospective EV buyers. Ultimately, EV adoption should accelerate as AI makes the EV ecosystem more attractive and competitive.

This Guidehouse Insights report describes the internal OEM AI applications used in the current generation of EV hardware and services as of 2020. It also documents pending or planned uses of AI in the EV value chain (second generation applications). The report also discusses third generation applications that are expected to offer further enhancements to existing or planned AI capabilities contributing to the overall EV experience, but they have yet to be implemented. In addition to these internal OEM use cases, this report provides an overview of EV-related AI opportunities around commercial fleet management, utility grid management, and EV charging integration.

KEY QUESTIONS ADDRESSED:

  • How is AI used in the manufacturing and operation of EVs?
  • How will AI improve the EV driving experience in the coming years?
  • What new features and capabilities will the EV supply chain and EV OEMs use to compete in the future?
  • How will AI address the objections presented by prospective EV customers and encourage them to acquire their first EV?
  • What should utilities/grid operators do to better prepare for EV adoption?

WHO NEEDS THIS REPORT:

  • General-purpose AI software vendors
  • EV battery and component manufacturers (hardware and software)
  • EV OEM manufacturers
  • Charging station service providers
  • Power utilities
  • Investor community

Table of Contents

1. Executive Summary

  • 1.1. Introduction
  • 1.2. Market Forecasts

2. Market Issues

  • 2.1. Introduction
    • 2.1.1. EV Power Technology Overview
    • 2.1.2. Market Trends
    • 2.1.3. Market Barriers
  • 2.2. AI-Based Applications in the EV Ecosystem
    • 2.2.1. Internal OEM Applications
      • 2.2.1.1. Improving Battery Design, Manufacturing, and Performance
        • 2.2.1.1.1. Uses of First Generation AI in Battery Design, Manufacturing, and Performance
        • 2.2.1.1.2. Uses of Second Generation AI for Battery Design, Manufacturing, and Performance
        • 2.2.1.1.3. Uses of Third Generation AI for Battery Design, Manufacturing, and Performance
      • 2.2.1.2. Improving the EV Experience and Reducing Objections to Buying EVs
        • 2.2.1.2.1. Uses of First Generation AI for the In-Vehicle Driver Experience
        • 2.2.1.2.2. Uses of Second Generation AI for the In-Vehicle Driver Experience
        • 2.2.1.2.3. Uses of Third Generation AI for the In-Vehicle Driver Experience
      • 2.2.1.3. Enhancing the EV Support System Experience
        • 2.2.1.3.1. Uses of First Generation AI for the EV Support System Experience
        • 2.2.1.3.2. Uses of Second Generation AI for the EV Support System Experience
        • 2.2.1.3.3. Uses of Third Generation AI for the EV Support System Experience
    • 2.2.2. Third-Party AI Solutions for the EV Ecosystem
      • 2.2.2.1. Commercial EV Fleet Support
        • 2.2.2.1.1. Uses of First Generation AI for EV Fleets
        • 2.2.2.1.2. Uses of Second Generation AI for EV Fleets
        • 2.2.2.1.3. Uses of Third Generation AI for EV Fleets
      • 2.2.2.2. Utility EV Integration Support
        • 2.2.2.2.1. Uses of First Generation AI Applications for Utilities
        • 2.2.2.2.2. Uses of Second Generation AI Applications for Utilities
        • 2.2.2.2.3. Uses of Third Generation AI Applications for Utilities

3. Key Industry Players

  • 3.1. Auto Motive Power
  • 3.2. Bidgely
  • 3.3. C4V
  • 3.4. Ford Motor Company
  • 3.5. General Motors
  • 3.6. Lucid Motors
  • 3.7. Nissan Motor Corporation
  • 3.8. Robert Bosch
  • 3.9. Tesla
  • 3.10. Texas Instruments
  • 3.11. TomTom

4. Market Forecasts

  • 4.1. Introduction
  • 4.2. Internal EV OEM Application Offering Forecasts by EVs Shipped
    • 4.2.1. Forecasts for In-Vehicle AI Applications
  • 4.3. Third-Party EV AI Solution Forecasts
    • 4.3.1. Forecasts for EV Fleet AI Applications
    • 4.3.2. Forecasts for Utility AI Applications for EV Planning
  • 4.4. Conclusions and Recommendations

5. Acronym and Abbreviation List

6. Table of Charts and Figures

7. Scope of Study, Sources and Methodology, Notes

LIST OF CHARTS AND FIGURES

  • Third-Party AI-Based Applications for EV Management Revenue, World Markets: 2020-2029
  • Sources of Electricity Generation, US: 2019
  • Historic and Forecast BEV Sales by Region, Base Scenario, World Markets: 2015-2029*
  • BEV Adoption Barriers, US: 2020
  • Demand for Electricity in California with Overlay of Preferred EV Charging Times, US: April 22, 2020
  • AI-Based Applications for Enhanced Range Estimation by Technology Generation, World Markets: 2020-2029
  • AI-Based Applications for EV-Aware Navigation by Technology Generation, World Markets: 2020-2029
  • AI-Based Applications for Charging Stations by Technology Generation, World Markets: 2020-2029
  • AI-Based Applications Revenue for Fleet Management Software, World Markets: 2020-2029
  • AI-Based EV Planning Applications Revenue for Utilities, World Markets: 2020-2029
  • Forecast EV Sales by Region, World Markets: 2020-2029

LIST OF TABLES

  • AI-Based Applications for Enhanced Range Estimation, World Markets: 2020-2029
  • AI-Based Applications for Enhanced Range Estimation, North America: 2020-2029
  • AI-Based Applications for Enhanced Range Estimation, Europe: 2020-2029
  • AI-Based Applications for Enhanced Range Estimation, Asia Pacific: 2020-2029
  • AI-Based Applications for Enhanced Range Estimation, Latin America: 2020-2029
  • AI-Based Applications for Enhanced Range Estimation, Middle East & Africa: 2020-2029
  • AI-Based Applications for EV-Aware Navigation, World Markets: 2020-2029
  • AI-Based Applications for EV-Aware Navigation, North America: 2020-2029
  • AI-Based Applications for EV-Aware Navigation, Europe: 2020-2029
  • AI-Based Applications for EV-Aware Navigation, Asia Pacific: 2020-2029
  • AI-Based Applications for EV-Aware Navigation, Latin America: 2020-2029
  • AI-Based Applications for EV-Aware Navigation, Middle East & Africa: 2020-2029
  • AI-Based Applications for Charging Station Experience Optimization, World Markets: 2020-2029
  • AI-Based Applications for Charging Station Experience Optimization, North America: 2020-2029
  • AI-Based Applications for Charging Station Experience Optimization, Europe: 2020-2029
  • AI-Based Applications for Charging Station Experience Optimization, Asia Pacific: 2020-2029
  • AI-Based Applications for Charging Station Experience Optimization, Latin America: 2020-2029
  • AI-Based Applications for Charging Station Experience Optimization, Middle East & Africa: 2020-2029
  • Forecast EV Sales by Region, World Markets: 2020-2029
  • AI-Based Applications Revenue for EV Fleet Planning Tools, World Markets: 2020-2029
  • AI-Based Applications Revenue for EV Planning Tools for Utilities, World Markets: 2020-2029
  • Third-Party AI-Based Applications for EV Energy Management Revenue, World Markets: 2020-2029
  • AI Applications in EV Battery Design, Manufacturing, and Performance
  • AI Applications for Improved EV Driver Experience
  • AI Applications for Enhancing the EV Support System Experience
  • AI Applications for the EV Support System for Commercial Fleets
  • AI Applications for Utilities Supporting EVs