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市场调查报告书

EV能源管理用AI:使用AI的EV电池的设计、制造、续航距离、导航最佳化、车队管理、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) 商品编码 967891
出版日期 内容资讯 英文 46 Pages; 38 Tables, Charts & Figures
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价格
EV能源管理用AI:使用AI的EV电池的设计、制造、续航距离、导航最佳化、车队管理、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日内容资讯: 英文 46 Pages; 38 Tables, Charts & Figures
简介

EV产业,为了提高EV体验积极应用AI技术。Guidehouse Insights 预计由于冠状病毒的大流行尽管造成销售台数一时后退,今后10年全部的地区EV销售将变得顺利。AI技术的使用,强化EV的效率与机能,提高EV OEM的竞争力,预期在克服未来的EV购买者的疑虑上日益发挥重要作用。AI为了使EV生态系统更富有魅力且有竞争力,最终预计加速EV的采用。

本报告提供EV能源管理AI的相关调查,目前这一代EV硬体和服务中使用的内部OEM AI应用以及EV价值链中待定或计划中的AI使用(第二代应用),还讨论了第三代应用程式,这些应用程式有望进一步增强现有或计划中的AI功能,从而为整体EV体验做出贡献,但尚未实现。除了这些内部OEM用例之外,本报告还概述了与EV相关的AI机会,涉及商业车队管理,公用电网管理和EV充电整合。

目录

第1章 摘要整理

  • 简介
  • 市场预测

第2章 市场问题

  • 简介
    • EV电力技术概要
    • 市场趋势
    • 市场障碍
  • EV生态系统的AI为基础的应用
    • 内部OEM应用
    • EV生态系统的第三方AI解决方案

第3章 主要企业

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

第4章 市场预测

  • 简介
  • 内部EV OEM应用提供预测:各EV出货
    • 汽车AI应用的预测
  • 第三方EV AI解决方案的预测
    • EV车队AI应用的预测
    • EV计划的公共事业AI应用的预测
  • 结论、建议

第5章 缩写、简称清单

第6章 图表

第7章 调查范围、调查来源、调查手法、注记

目录
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