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Current Funded Projects

Comprehensive Mobility Report for the Trucking & Transit Sector

This project aims to develop a strategic, data-driven report that assesses the current mobility landscape in the trucking and transit sectors. The focus is on identifying bottlenecks, opportunities, and challenges in these sectors to enhance operational efficiency, reduce emissions, and improve overall service reliability. The report will address industry concerns such as congestion, rising fuel costs, and the need for innovative, sustainable technologies. Additionally, it will consider societal issues, including air pollution, public health, and infrastructure degradation. The project will also provide actionable recommendations and propose technology-driven solutions like electrification and autonomous vehicle integration to ensure future scalability. 

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  • PI: Sabya Mishra

  • Timeline: January 1, 2025 - December 31, 2025

Electrifying School Bus Fleets: A Data-Driven Transition Plan

The transition to electric vehicles (EVs) presents an urgent opportunity to reduce pollution and improve air quality, particularly in environments where young people are most vulnerable, such as schools. Diesel-powered school buses contribute significantly to emissions, negatively impacting both student health and the surrounding environment. This project aims to overcome the challenges associated with the high costs of EV adoption, limited charging infrastructure, and the complexities of integrating electric vehicles into existing fleet operations. The proposed project will develop a comprehensive, phased transition plan, making use of advanced data-driven methodologies to achieve operational and cost-efficiency for a local school district's bus fleet electrification project. Additionally, this project’s goal is to understand the business case for commercial truck fleet electrification including the opportunities, barriers, and strategies. This study will help us understand both the major barriers to electrified truck investments as well as the potential opportunities for deploying them in supply chains. Key study deliverables will be a CEAT managerial report on investing in and transforming supply chains using electric trucks as well as an “Electrified Trucking” Industry index.

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  • PIs: Hasan Ali, Mark Frohlich

  • Timeline: January 1, 2025 - December 31, 2025

Transverse Homopolar AC Machine Prototyping & Testing

The goal of this project is to build and test a protype of a novel class of electric machines called a Transverse Homopolar AC Machine. This machine has a robust rotor due to the absence of permanent magnets, which are instead located on the stator and, as both conductors and permanent magnets are located on the stator, it can be cooled directly, facilitating the use of dysprosium free magnets, lowering the machine’s cost. Presently a detailed design code has been developed and validated using commercial 3D FEA codes. A 10 kW prototype with a constant power speed range of 2,000 to 10,000 rpm has been designed,  and will utilize innovative additive manufacturing techniques to construct the frame and metal laser 3D printing of the magnets.

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  • PIs: Scott Sudoff, Jing Zhang

  • Timeline: January 1, 2025 - December 31, 2025

A Digital Twin Simulation Study for Connected Eco-Driving Systems on Commercial Vehicles

This project will develop a high-fidelity digital twin simulation platform to evaluate connected eco-driving systems for commercial vehicles in realistic freight environments. Using detailed corridor models, signal timing data, and heavy-duty truck representations for both internal combustion and battery electric vehicles, the platform will test strategies such as Green Light Optimal Speed Advisory and Eco-Approach and Departure under varied traffic and operating conditions. Deliverables include the simulator, vehicle models, corridor digital twins, implemented algorithms, and a performance evaluation report. The platform offers industry a cost-effective way to assess V2X-enabled freight strategies, energy performance, operational efficiency, and emissions impacts before deployment.​

  • PIs: Ziron Wang, Lingxi Li, Sabya Mishra Myounggyu Won

  • Timeline: January 1, 2026 - December 31, 2026

Safe Fast Charging Algorithm and Performance Assessment of Batteries in Electric Freight Vehicle Applications

This project develops and validates a safe fast-charging algorithm for lithium-ion batteries used in electric freight vehicles. The work addresses a major barrier to truck electrification by reducing charging time while protecting battery health. The approach integrates battery state-of-health modeling, including solid-electrolyte interphase growth and irreversible lithium plating, together with temperature and current constraints. It will be assessed on high-capacity battery packs using realistic freight operating conditions and power-hardware-in-the-loop testing. Expected outcomes include a working charging algorithm with integrated health prediction, validation results, and insights that could improve fleet productivity, extend battery life, and support broader commercial EV adoption nationwide.​

  • PIs: Sohel Anwar, Alex Headley

  • Timeline: January 1, 2026 - December 31, 2026

Tactical Matching of Truck Routes

This project develops a tactical route-matching approach to reduce empty truck travel across recurring freight lanes. Rather than focusing on one load at a time, it uses network-wide optimization and decision-support tools to identify stable backhaul opportunities and improve coordination across shippers. The effort will produce an optimization model, a documented decision-support system, anonymized route data for testing, and recommendations for integration with existing freight systems. By reducing empty miles, the approach could lower fuel consumption, operating costs, and emissions while improving asset utilization. The project aims to make freight logistics more collaborative, efficient, and scalable for long-term industry application.

  • PIs: Mohamed Salama, Sabya Mishra

  • Timeline: January 1, 2026 - December 31, 2026

Smart Vehicle-to-Grid Integration and Managed Charging Framework for Heavy-Duty Fleet Electrification

This project develops a smart managed-charging and vehicle-to-grid framework for heavy-duty fleet electrification. It addresses the grid impacts of concentrated depot charging by combining charger-level data, grid-capacity limits, and utility pricing to forecast demand, optimize charging schedules, and reduce peak stress. The framework will identify charging hotspots, quantify gaps between grid capacity and fleet demand, and support lower-cost charging aligned with renewable-rich periods. Optional vehicle-to-grid functionality will help shave peaks and improve resilience. Deliverables include a managed-charging control platform, predictive load models, a grid-stress dashboard, and implementation guidance for fleets, utilities, manufacturers, and public-sector stakeholders.

  • PIs: Hasan Ali, Sabya Mishra, and Satish Ukkusuri

  • Timeline: January 1, 2026 - December 31, 2026

Enhancing Roadside Safety through Virtual Reality Simulation and Intelligent Warning Systems for Commercial Motor Vehicles

This project develops a virtual reality and intelligent warning system framework to improve roadside safety for commercial motor vehicles during emergency stops. Using immersive highway simulations, it will compare manual warning triangles, semi-automated systems, and fully automated warning technologies under varying traffic, lighting, and weather conditions. The research will measure surrogate safety metrics such as time-to-collision, time headway, lateral clearance, and exposure duration, then apply machine learning to classify risk and quantify safety improvements. Deliverables include a validated VR simulation platform, comparative performance analysis, risk-prediction models, and implementation guidance that can support fleet training, technology adoption, and future safety policy development.

  • PIs: Sabya Mishra, Ziran Wang

  • Timeline: January 1, 2026 - December 31, 2026

Center for Freight & Logistics Efficiency with Electrified & Automated Trucking

Purdue University
University of Memphis

 
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