Hybrid electric vehicles (HEVs) are considered to be one of the energy-efficient technologies for near-term sustainability of the transportation sector. Over the years, research has focused on improving fuel economy (FE) for a given drive cycle, but FE variability over a realistic range of real-world driving patterns has been generally overlooked, and this can lead to FE benefits not being fully realized in real-world usage. No systematic methodology exists to reduce FE variability by design optimization of powertrain components. This study proposes a methodology of powertrain component optimization to reduce the FE variability due to variations in driving patterns. In the proposed methodology, powertrain components are optimum over a range of driving patterns of different traffic conditions and driving styles simultaneously. The proposed methodology demonstrates the potential to reduce FE variability by up to 34% over six driving patterns of different traffic conditions and driving styles.