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Title ImagePublic Abstract


DE-SC0020744: Connected Energy Management System to Enable Battery Electric Last-Mile Delivery Vehicles

Award Status: Active
  • Institution: Exergi Predictive LLC, Minneapolis, MN
  • DUNS: 1173768510000
  • PM: Gupte, Prasad
  • Most Recent Award Date: 07/13/2020
  • Number of Support Periods: 1
  • PI: Farley, Toni
  • Current Budget Period: 06/29/2020 - 06/28/2021
  • Current Project Period: 06/29/2020 - 06/28/2021
  • Supplement Budget Period: N/A

Public Abstract

Connected Energy Management System to Enable Battery Electric Last-Mile Delivery Vehicles—Intelengine, LLC, 1333 Juno Avenue, Saint Paul, MN 55116-1628

Eddie Arpin, Principal Investigator,

Shawn Haag, Business Official,

Amount:  $200,000.00


In this proposed SBIR project, Intelengine, LLC will develop a connected energy management system (c-EMS) for application in the nascent electrified last-mile delivery truck market, building on its current product offering for range-extended hybrid delivery trucks. With increasing desire to decarbonize, lower maintenance costs, and meet increasing regulatory requirements in urban areas, delivery fleets are motivated to electrify large portions of their fleets. Although the driving range of electric vehicles (EVs) is increasing as battery technology matures, many delivery routes are not possible to achieve with current vehicles. Range anxiety is therefore a key factor in steering fleet operators away from adopting electric vehicles. To solve this challenge, the goal of the proposed project is to accurately predict the range of last-mile delivery EVs for a given route and to reduce the need for expensive on-route charging. The primary technical objectives of this Phase I project are to: 1) Use collected data from delivery routes to model last-mile electric delivery vehicle energy use and battery energy use on upcoming routes; 2) Develop and test a c-EMS that takes input data including desired route and exogenous data, and predicts vehicle range and on-route charging requirements; 3) Quantify potential cost benefits to fleet owners of implementing EV for package delivery with and without c-EMS using a techno-economic analysis; and 4) Work with a university research laboratory to develop new machine learning algorithms for predicting battery SOC trajectory for a future route using historical and exogeneous data. With the immense growth of e-commerce in the US, most consumers will do at least some of their shopping online and have their goods shipped using a last-mile delivery service. Increasing the number of electrified vehicles used in those deliveries has significant impact not only in terms of fuel use, but also will reduce local criteria pollutant emissions and noise currently emitted by gasoline or diesel delivery trucks. This positively impacts public health and reduces delivery vehicles’ negative impact on the environment more broadly. This effort proposes to realize and test a c-EMS system that will reduce range anxiety among fleet operator companies and allow them to incorporate electric delivery vehicles at a higher rate. A Phase II project is envisioned to refine the technology further and deploy it as a fully demonstrable product and service. A Phase III effort would continue to refine the technology to grow Intelengine’s c-EMS into a viable and profitable service.

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