As electric vehicles (EVs) gain traction globally, understanding their real-world performance under diverse urban driving conditions becomes vital, particularly in emerging markets like Malaysia. This study introduces an innovative simulation-based approach using ADVISOR software to evaluate EV efficiency, energy consumption, and powertrain behavior across two localized driving cycles: the Kuala Terengganu Driving Cycle (KTDC) and the Ipoh Driving Cycle (IDC). Both driving cycles were developed through a genetic algorithm-based optimization of actual traffic data, offering a more accurate reflection of Malaysian urban traffic dynamics. The analysis highlights key performance metrics such as motor torque, power loss, battery load, and state-of-charge variations, revealing significant differences in EV behavior under varied urban settings. Results from this study provide critical insights for vehicle manufacturers, urban planners, and policymakers aiming to accelerate sustainable transport adoption in Southeast Asia. The approach demonstrates a scalable framework for localized EV testing, supporting smart city development and mitigation of environmental impact.