Commercial Vehicle (CV) market is growing rapidly with the advancement of Software-Defined Vehicles (SDVs), which provide greater level of flexibility, efficiency and integration of AI & cutting-edge technology. This research provides an in-depth analysis of E&E architecture of CVs, focusing on the integration of SDV-based technology, which represents the transition from hardware-focused to a more dynamic, software-focused methodology. The research begins with the fundamental concepts of E&E architecture in CVs, including virtualization, centralized computing, feature based ECU, CAN and modular frameworks which are then upgraded to meet various operational and customer requirements. The capacity of SDV-based architecture designs to scale to handle heavy duty commercial vehicles is a primary focus, with an emphasis on ensuring the safety and security, to defend against potential vulnerabilities. Furthermore, the integration of real-time data processing capabilities and advanced E&E architecture is proposed, considering features available in the current and potential future market. We also examine current and future market trends in CVs related to the E&E architecture, discussing advanced features such as OTA, fleet management, telematics, and more. This research focuses on adding SDV features to upcoming CVs, with the goal of improving vehicle performance. Future considerations include the integration of autonomous driving technology and the growing significance of cloud and edge computing technology in enhancing commercial vehicles' decision-making capabilities. This research offers a comprehensive understanding of how SDV architecture is poised to revolutionize the heavy-duty commercial vehicle industry, providing insights into how it will make CVs more automated, connected, and efficient.