EV ASSIST – Feasibility Study of Vehicle-User-Network Optimisation

EV ASSIST — 车辆-用户-网络优化的可行性研究

• 批准号: 77500
• 金额: $ 25.01万
• 依托单位: YOU. SMART. THING. LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=77500
• 关键词: EV; ASSIST; Feasibility; Study; Vehicle

**EV Assist -- Feasibility Study of Vehicle-User-Network Optimisation**The aim of the project is to assess the technical feasibility and commercial potential of "EV Assist", a personalised travel assistant that will use artificial intelligence and machine learning to increase use of electric vehicles and infrastructure.Every car that is replaced with an electric vehicle contributes a CO2 saving of around 133.1g/km. Lower running costs, less maintenance, a lower carbon footprint and cleaner air all add up to significant social, economic, and environmental benefits. But the EV industry is struggling to achieve the necessary adoption to realise these benefits.'Range anxiety' is at the route of the EV paradox. A perceived lack of access to charge points among would-be EV users, discourages them from switching from traditional combustion engine vehicles, with their established fuel supply chain. This could be overcome with additional charge-point infrastructure but currently operators have no means of capturing granular demand, which is key to calculating return on investment.The UK Government is currently picking up the bill, offering tax incentives, congestion and clean air zone concessions to drive EV adoption. This is costly and unsustainable.EV ASSIST will be designed to enable real-time information exchanges between electric vehicle owners and charge point infrastructure operators regarding near-term charging requirements and the availability of charging infrastructure at any given time.The successful realisation of EV ASSIST can improve the overall customer experience of travelling by EV, directly addressing range anxiety, and helping operators extract maximum value from their charging assets by optimising utilisation per customer. In combination, these EV ASSIST enabled outcomes can make a significant contribution to supporting the UK's electric transition over the next decade.A 6-month research programme has been put together by partners to investigate vehicle-user-network optimisation through desktop research, EV community engagement, and Proof-of-Concept test exercises asking:* How can information be most efficiently captured and shared by EV ASSIST?* How to incentivise end-users to share their EV travel requirements with operators?* How can operators most effectively exploit EV ASSIST generated demand forecasts?* How to scale and commercially exploit EV ASSIST to best effect?* What is the precise impact EV ASSIST can have on the UK government's "Road to Zero" strategy?The project is led by Birmingham-based travel demand and route optimisation platform 'You. Smart. Thing.' (YST) and supported by Transport for West Midlands ("TfWM"), owner and operator of charge point assets across the region.

**EV Assist—车辆-用户网络优化可行性研究**该项目的目的是评估“EV Assist”的技术可行性和商业潜力，这是一种个性化的出行助手，将使用人工智能和机器学习来增加电动汽车和基础设施的使用。每辆被电动汽车取代的汽车每公里可减少约133.1克的二氧化碳排放。更低的运行成本、更少的维护、更低的碳足迹和更清洁的空气都能带来显著的社会、经济和环境效益。但电动汽车行业正在努力实现必要的采用，以实现这些好处。“里程焦虑”是电动汽车悖论的根源。在潜在的电动汽车用户中，由于缺乏充电点，他们不愿放弃传统的内燃机汽车，因为他们已经建立了燃料供应链。这可以通过额外的充电点基础设施来解决，但目前运营商没有办法捕捉到颗粒需求，而这是计算投资回报的关键。英国政府目前正在买单，提供税收优惠、拥堵和清洁空气区优惠，以推动电动汽车的普及。这是代价高昂且不可持续的。EV ASSIST旨在使电动汽车车主和充电点基础设施运营商之间能够实时交换有关近期充电需求和充电基础设施在任何给定时间的可用性的信息。EV ASSIST的成功实现可以改善电动汽车出行的整体客户体验，直接解决里程焦虑，并通过优化每位客户的利用率，帮助运营商从充电资产中获取最大价值。综上所述，这些支持EV ASSIST的成果可以为支持英国未来十年的电动化转型做出重大贡献。合作伙伴已经制定了一项为期6个月的研究计划，通过桌面研究、电动汽车社区参与和概念验证测试练习来调查车辆用户网络优化，这些测试练习包括：* EV ASSIST如何最有效地捕获和共享信息？*如何鼓励终端用户与营办商分享他们的电动车出行需求？*运营商如何最有效地利用EV ASSIST生成的需求预测？*如何扩大EV ASSIST的规模并将其商业化以达到最佳效果？* EV ASSIST对英国政府的“零排放之路”战略有何确切影响？该项目由伯明翰的旅游需求和路线优化平台You牵头。聪明。事情。’（YST），并得到西米德兰兹郡交通局（“TfWM”）的支持，该公司是该地区充电点资产的所有者和运营商。