The recent automotive industry trend towards electrification has created new challenges for NVH engineers. These challenges stem from new powertrain architectures and their complex interactions, the governing control strategies which aim to optimize energy management, and new unmasked sources of excitation. Additionally, vehicle manufacturers are attempting to reduce hardware testing in order to rapidly satisfy increasing production demand and to minimize its costs. Hence, to meet the above-mentioned challenges up front in the development process of Hybrid Electrical Vehicles (HEVs) while balancing competing design objectives of drivability, durability and NVH, a simulation-led design and optimization is required. NVH problems are often the result of mechanisms that originate through complex interactions between different physical domains (flow, electromagnetic, structural/mechanical, control logic, etc.) and the assembly of individual components into a complete system. Therefore, accurate system-level integrated models are becoming a requirement to solve modern NVH problems. Combining the optimal balance between simulation and experimental data, this article describes a joint effort between Ford and Gamma Technologies to develop a general methodology to perform full-vehicle low frequency NVH analysis. Using GT-SUITE software, a non-linear multi-physics simulation model of a rear wheel drive HEV was created. The model was exercised to accurately evaluate the effects of powertrain control strategy and component selection on low-frequency NVH performance during a tip-in regeneration, downshifting and in-gear acceleration maneuvers while minimizing the computational cost.