This work reports the experimental and numerical study of the thermal management of Li-ion battery packs under the context of electric vehicle (EV) or hybrid EV (HEV) applications. Li-ion batteries have been extensively demonstrated as an important power source for EVs or HEVs. However, thermal management is a critical challenge for their widespread deployment, due to their highly dynamic operation and the wide range of environments under which they operate. To address these challenges, this work developed several experimental platforms to study adaptive thermal management strategies. Parallel to the experimental effort, multi-disciplinary models integrating heat transfer, fluid mechanics, and electro-thermal dynamics have been developed and validated, including detailed CFD models and lumped parameter models. The major contributions are twofold. First, this work developed actively controlled strategies and experimentally demonstrated their effectiveness on a practical sized battery pack and dynamic thermal loads. The results show that these strategies effectively reduced both the parasitic energy consumption and the temperature non-uniformity while maintaining the maximum temperature rise in the pack. Second, this work established a new two dimensional lumped parameter thermal model to overcome the limitations of existing thermal models and extend their applicable range. This new model provides accurate surface and core temperatures simulations comparable to detailed CFD models with a fraction of the computational cost. / Ph. D. / Li-ion batteries have been widely used today as power source of electric vehicles (EV) or hybrid electric vehicles (HEV). Thermal management represents an important issue for the safe and efficiency of Li-ion batteries in EVs and HEVs. Thermal issues can lead to decreased energy efficiency, reduced battery lifetime, and even catastrophic failures. However, effective thermal management of Li-ion batteries is challenging due to several reasons, including the highly dynamic operation of the batteries and the wide range of ambient conditions under with the vehicles operate. To address these challenges, this work studied the thermal management problem through both experimental and numerical methods. Experimentally, actively controlled strategies have been designed and tested on our customized experimental platforms, and the results demonstrated the effectiveness such strategies. Numerically, multidisciplinary models have been developed and validated to provide comprehensive information of battery operation, and furthermore to simulate operation under extreme conditions that are difficult study experimentally. This dissertation reports both the experimental and numerical results, with a detailed analysis of their implications and applications.