Year: 2026
Type: conference-paper
Abstract: The shift toward electrified vehicle powertrains and rising performance expectations are driving innovation in battery systems. Meeting targets for energy density, power output, safety, and service life requires rapid exploration of new cell chemistries, integration strategies and thermal concepts. Early-stage design is particularly challenging due to limited availability of data and the inefficiency of traditional CAE simulations and prototyping. To address this, a MATLAB-based method has been developed that enables efficient bottom-up design of battery systems from cell to module to system level. This approach automates key tasks such as electrical configuration, material selection, and geometric arrangement, allowing fast evaluation of feasible design variants. It also incorporates subsystems such as housing, thermal management, BMS hardware, and E/E components, generates simplified 3D models and calculates key performance indicators (KPIs) including energy density, power capability, and system weight. These are benchmarked against predefined targets to identify the best possible concepts. This method supports further assessments such as LCA, cost, and safety analysis, and guides the selection of optimal configurations. Use cases demonstrate the value of this method through enabling systematic comparison and supporting early decision-making for both academic and industrial stakeholders.
Source: Lecture notes in mobility
Institution: FEV (Germany)
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7224937267