Overcoming Challenges in the Transition Towards Battery Electric and Software-Intensive Modular Heavy-Duty Vehicles

The automotive industry is undergoing a significant transition, where the development of Battery Electric Vehicles (BEV) and the increasing use of intelligent vehicle functions are transforming vehicles into advanced Cyber-Physical Systems. For heavy-duty OEMs, this transition challenges a Product Development (PD) heritage inherent in an ecosystem of established processes, IT systems, and organization structures. This study primarily comprises semi-structured interviews, conducted at a heavy-duty OEM, and a focused literature search. The study contributes by the following: (i) identifying key PD challenges in the ICE–BEV transition, (ii) outlining obstacles in adopting Model-Based Systems Engineering (MBSE) for managing architectural complexity, and (iii) synthesizing recommendations for architecture-driven collaboration. Interview findings, highlighted intertwined challenges such as fragmented architecture descriptions across physical and software domains, weak continuity between early-phase system context and detailed design, and collaboration constrained by inconsistent terminologies, strained communication channels, and manual reconciliation of architectural information through documents and disconnected tools. These factors hinder function-component traceability and concurrent development across domains. While MBSE is often recommended to address such issues, practical obstacles are noted, including trade-offs between modeling effort and fidelity, limited support for early spatial layout integration, difficulties in bridging physical and software architectures, and the limited integration of document-based practices preferred in early conceptual phases. Based on these insights, the study recommends architecture-driven collaboration anchored in a federated vehicle-architecture description, supported by a distributed systems-engineering function. A layered development approach combining document artifacts with progressively rigorous MBSE is advised for early-phase agility, later-stage traceability, and structured information flow.