Telematics-based Managed Charge Optimization for Equitable EV Adoption in the Residential Rental Segment

As electric vehicle (EV) adoption accelerates, it will become increasingly important to have accurate data on where, when and how much EVs are charged. Charging data will provide a basis for evaluating current EV infrastructure, such as installed charger utilization, and plans for expansion, such as rebates, incentives and managed charging. City and utility transportation electrification plans will need to simultaneously ensure affordable and equitable transportation options, well-planned charging infrastructure and a dependable electric grid as demand from EVs grows. To that end, this project will develop a novel decision support capability based on EV charging data collection to help evaluate current EV-related infrastructure and help predict how to expand it effectively, particularly for the residential rental market. A lack of charging infrastructure for residential renters is a roadblock to equitable EV adoption. Currently there are few incentives for building owners to install chargers, so tenants who might wish to own an EV will not have access to charging at their home. This is particularly true in low income and disadvantaged communities, in which a large portion of the population rent their homes. Our proposed solution will make use of a recently developed capability to collect real-time data on EV drivers’ charging and travel patterns, using hardware-free, two-way communication with each EV’s onboard data (telematics) system. Our innovation is to analyze the telematics data for decision support, helping to minimize EV charging costs both to the driver, through charging when energy costs are lowest, and to the energy supplier, through a flatter demand curve and less need for added infrastructure. Aggregating data on individual vehicle distances traveled, charge durations and states of charge will enable quantitative estimates of reductions in transportation costs, energy and emissions from EV adoption initiatives in specific communities. A mature capability will ingest demographic and infrastructure data, along with real-time telematics data, and provide monitoring and modeling of the EV landscape in a targeted geography over time. Stakeholders can see the "state of EVs" at any given time and for any geographic location, and more confidently forecast into the future to help design optimal adoption incentives specifically for residential rental customers. We are partnering with the city of Colorado Springs and with its municipal utility, Colorado Springs Utilities, plus Drive Clean Colorado (part of DOE’s Clean Cities program. Colorado Springs recently completed its Electric Vehicle Readiness Plan (EVRP), so this provides us a unique opportunity to test the proposed capabilities in a real-world setting, while supporting the EV rollout plan for the city. In Phase I, we will focus on demonstrating the feasibility of 1) supplementing demographic and infrastructure data on Colorado Springs obtained from our partners with telematics-derived charging data and 2) using the combined data to help evaluate current infrastructure and guide effective expansion. We will also work with the city’s Community Development department during Phase I to understand the specific demographics of renters and low-income households in the city in anticipation of a possible Phase II pilot project. Then in Phase II we will work with the utility to run additional outreach and recruitment campaigns to increase the number of EV participants, assimilating data and developing a prototype design for one or more identified multi-unit dwellings, modeling appropriate incentive structures, costs of installation and anticipated reductions in transportation costs, energy and emissions.