SBIR Phase II: Adaptive Charging Network for EV and Energy Services

该项目更广泛的影响/商业潜力将满足两个社会需求。它将以最低成本实现电动汽车(EVS)的大规模充电基础设施，并将提供能源服务，以帮助整合可再生能源。这一点至关重要，因为发电和运输总共消耗了美国近三分之二的能源，排放了美国一半以上的温室气体。因此，要大幅减少温室气体排放，将需要我们的交通工具实现电气化，并使用可再生能源发电。加州要求到2025年拥有150万辆零排放汽车，目前全国一半的电动汽车都在加州。如果该项目成功，当大规模部署时，拟议的技术可能每年为CA节省1.44亿美元的运营成本，并在CA在2025年达到其雄心勃勃的目标时节省11亿美元的资本成本。这有助于每年减少加利福尼亚州的温室气体550万吨。因此，该项目将在清洁交通和清洁能源方面产生影响。这个小型企业创新研究(SBIR)第二阶段项目将开发一种自适应电动汽车充电系统，可以实施电动汽车充电行业目前无法实现的许多创新。它将为站点主机提供回收成本的解决方案，共同优化现场分布式能源，如太阳能电池板和电池组，最大限度地降低站点主机的运营成本和司机的充电成本，并在基础设施容量限制的情况下，最佳地权衡不同驱动器和站点主机的偏好和限制。这些技术将基于独特的实时传感、通信和控制能力，以及先进的优化和学习算法。这些技术将以最低的基础设施和运营成本提供目标充电能力，以及为电网提供能源服务的平台。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this project will address two societal needs. It will enable mass charging infrastructure for electric vehicles (EVs) at minimal cost, and will enable the provisioning of energy services to help integrate renewable energysources. This is critical as electricity generation and transportation together consume close to two-thirds of all US energy and emit more than half of all US greenhouse gases. To drastically reduce greenhouse gases will therefore require electrification of ourtransportation and renewable generation of our electricity. California (CA) has a mandate to have 1.5 million zero-emission vehicles by 2025 and, currently, half of the nation's EVs are in CA. If the project is successful, the proposed technology, when deployed at scale,can potentially save CA $144M annually in operating costs and $1.1B in capital cost when CA reaches its ambitious goal by 2025. This can help reduce greenhouse gases annually in CA by 5.5 million metric tons. This project will therefore make an impact in both cleantransportation and clean energy.This Small Business Innovation Research (SBIR) Phase 2 project will develop an adaptive EV charging system that can implement a number of innovations that are not currently available in the EV charging industry. It will offer a site host a solution to recover costs,jointly optimize onsite distributed energy resources such as solar panels and battery banks, minimize operating cost for site host and charging cost for drivers, and optimally trade off preferences and constraints of different drivers and of the site host, subject toinfrastructure capacity constraints. These technologies will be based on unique real-time sensing, communications, and control capabilities, as well as advanced optimization and learning algorithms. These technologies will provide a target charging capacity at minimal infrastructure and operating costs, as well as a platform for energy services to the grid.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.