Energy Cost Optimization Framework for EV Logistics Enterprise
Summary
USPTO has published patent application US20260099787A1, filed by Tata Consultancy Services Limited on June 24, 2025, for an AI-driven optimization framework that minimizes energy costs for electric vehicle (EV) logistics operations. The framework addresses cyclic dependency between electricity procurement costs and vehicle routing by iteratively optimizing routing costs and energy procurement from different energy sources.
What changed
USPTO has published patent application US20260099787A1, filed by Tata Consultancy Services Limited, for an AI-driven optimization framework that minimizes energy costs for electric vehicle (EV) logistics operations. The framework addresses cyclic dependency between electricity procurement costs and vehicle routing by iteratively optimizing routing costs and energy procurement from different sources.
This patent application is relevant for logistics companies operating EV fleets and technology firms developing fleet management solutions. The disclosed methods may influence future competitive developments in AI-powered logistics optimization and energy management systems.
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Apr 11, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
METHOD AND SYSTEM FOR ENERGY COST OPTIMIZATION FRAMEWORK FOR A LOGISTIC ENTERPRISE
Application US20260099787A1 Kind: A1 Apr 09, 2026
Assignee
Tata Consultancy Services Limited
Inventors
ANSHU KUMAR, PRASANT KUMAR MISRA, VISHNU PADMAKUMAR MENON, VENKATESH SARANGAN
Abstract
The embodiments of the present disclosure herein address unresolved problems of cyclic dependency between cost of power procurement and routing of one or more electric vehicles (EVs) of a logistic enterprise. Embodiments herein provide a method and system for an optimization framework to overcome a cyclic dependency between cost of power procurement and routing of electric vehicles (EVs) of a logistic enterprise. The optimization framework comprises two independent routines, coupled through an exchange of parameter values. First routine optimizes routing cost of the EVs to satisfy delivery constraints by assuming that the average EV charging cost is known. This is given as input to a second routine that optimizes electricity procurement cost from different energy sources by assuming that the EVs routes are fixed. The output from the second routine is then given back as input to first routine, and the procedure iterates till a stopping criteria is reached.
CPC Classifications
G06Q 10/06315 G06N 3/086 G06Q 10/047
Filing Date
2025-06-24
Application No.
19248320
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