Cloud Connected Delivery Vehicles: Boosting Fuel Economy using Physics-Aware Spatiotemporal Data Analytics and Realtime Powertrain Control

PI: Will Northrop, Mechanical Engineering                                          
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Co-PI: Shashi Shekhar, Computer Science & Engineering

Pengyue Wang, PhD student, Mechanical Engineering

Yan Li, PhD student, Computer Science & Engineering


Major Technical Achievement

Connected Energy Management System (C-EMS) for electrified delivery trucks that achieved greater than 20% improvement in MPGe.

Technical Accomplishments

Two Interventions: C-EMS and Energy Efficient Routing (EER)

  • EER:  Reduced energy use between set origin-destination pairs with a time penality
  • C-EMS: Minimized fuel consumption through practical rule-based algorithms

Tech-to-Market Accomplishments

  • Partnership with Workhorse Group to implement C-EMS as an API on all 300 E-GEN vehicles in the UPS fleet
  • Pivoting towards battery electric vehicle trucks
  • Formation of Intelengine, LLC, as a software as a service (SAS) company

This project developed technology to improve the fuel efficiency of last-mile delivery vehicles through real-time powertrain optimization using two-way vehicle-to-cloud connectivity. The project was led by the University of Minnesota and represents a collaboration between engine research and computer and data science.

Funding was provided by the U.S. Department of Energy's Advanced Research Projects Agency–Energy (ARPA–E) NEXTCAR program.


Large delivery vehicle fleet operators such as UPS use analytics to assign routes to minimize fuel consumption. Algorithms mine historical data collected from vehicles to determine routes before a driver leaves a distribution center.

UPS has also invested in E-GEN series electric-powertrain vehicles produced by Workhorse Group Inc. that allow pure electric driving for extended periods of time and use a small range-extending gasoline engine generator to charge the battery, allowing longer routes. Workhorse uses a two-way telemetry system—Metron—on the UPS E-GEN vehicles for diagnostics and fault prediction.

However, neither the current UPS routing algorithms nor the Metron telemetry system interact with the vehicle directly to improve the fuel economy in real time. This project will lead to a greater than 20 percent improvement in the fuel economy of a baseline 2016 E-GEN delivery vehicle by integrating routing, two-way telemetry, and cloud computing.

More information about our Vehicle Powertrain and Routing Co-Optimization research, please visit

Project Partners