Volume 64

Forecasting EV Transitions under Policy Scenarios in Pakistan using System Dynamics Modelling Mazhar Uddin , Richard Blanchard , James Fleming , Zhengyu Lin

Abstract

The government of Pakistan has announced Electric Vehicle (EV) policies to encourage faster adoption. Such policies set certain targets, but not even 5% of these targets were met as announced in the National Electric Vehicle Policy (NEVP) 2019. The recently announced New Energy Vehicle (NEV) Policy 2025 also lacks evidence-based foundations, with targets that appear ambitious but unrealistic as highlighted by Pakistan Automobile Industry. This research employs System Dynamic Modelling (SDM) to forecast impact of various policies and generate scenarios for wider EV adoption in Pakistan. Four scenarios were set in this paper: scenario 1 (Business as Usual), scenario 2 (Government Support and Finance Policy), scenario 3 (Carbon Trading and Emission Trading System) and scenario 4 (a mixture of policies). In 2020, EV sector was still characterized by its early-stage development, reflecting limited technological advancement and infrastructure readiness. The SDM results indicate that, by 2040, the total number of EVs will amount to 120,000, 202,000, 146,000 and 202,000 under scenarios 1-4, respectively. Findings indicate that, the country’s policies, such as financial schemes, play an important role in shaping Pakistan’s EV market penetration. The analysis result demonstrates that subsidies and carbon pricing drive significant adoption gains, though integrated policies yield the most substantial impact.

Keywords Electric Vehicles, National Electric Vehicle Policy, New Energy Vehicle Policy, System Dynamic Modelling, Policy Scenarios, Casual Loop Diagrams