With the increasing demand for Battery Electric Vehicles (BEVs) capable of extended mileage, optimizing their efficiency has become paramount for manufacturers. However, the challenge lies in balancing the need for climate control within the cabin and precise thermal regulation of the battery, which can significantly reduce a vehicle's driving range, often leading to energy consumption exceeding 50% under severe weather conditions. To address these critical concerns, this study embarks on a comprehensive exploration of the impact of weather conditions on energy consumption and range for the 2019 Nissan Leaf Plus. The primary objective of this research is to enhance the understanding of thermal management for BEVs by introducing a sophisticated thermal management system model, along with detailed thermal models for both the battery and the cabin. These models are seamlessly integrated into a 2019 Nissan Leaf Plus BEV model developed in Autonomie, allowing for a holistic assessment of the influence of weather conditions on the driving range. The proposed model encompasses a mono-zonal model for the cabin, providing estimations of cabin temperature, humidity, and thermal requirements. Additionally, a battery thermal model for pouch-type cells, employing a 2D discretization approach with a nodal framework, is presented to predict battery temperature dynamics. Furthermore, a comprehensive thermal management system is integrated into the model, featuring a vapor compression cycle equipped with a PTC resistor. The study leverages these developed models within the Simulink framework and utilizes the Autonomie Software for rigorous evaluation of energy consumption and driving range. Various driving cycles and a range of ambient temperatures (-18°C, -7°C, 22°C, and 35°C) are considered in the analysis. To validate the models, the study draws upon experimental data collected from a 2019 Nissan Leaf subjected to extreme temperature conditions in the Environmental Test Cell at Argonne National Laboratory.