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Conceptual Framework and Performance Forecasting of a Terrain-Adaptive Plug-and-Play Range Optimization System for Electric Four-Wheelers

Year: 2025

Type: article

Abstract: This research presents a conceptual framework and predictive simulation for a terrain-adaptive, plug-and-playenergy optimization module designed for electric four-wheelers. Building upon proven success in two-wheeler EVs, this paperextends the architecture to heavier, multi-axle platforms. By integrating AI-based terrain analysis, driving pattern recognition,and intelligent power routing, the proposed system aims to deliver up to 22–28% improvement in driving range withoutmodifying core drivetrain components. Simulations based on real urban and semi-urban Indian driving data validateperformance forecasts. The system is particularly relevant to passenger EVs, fleet operators, and last-mile delivery vehicles ininfrastructure-limited markets.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15703703

Author: Pandya, Anay Sunilkumar

Language: English

Topic: Electric and Hybrid Vehicle Technologies

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities, Affordable and clean energy

Open Access status: green

OpenAlex ID: W6930649126

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