These slides were presented at the NAFEMS World Congress 2025, held in Salzburg, Austria from May 19–22, 2025.

Abstract

Limiting carbon footprints is a global issue that has a huge impact on companies. Particularly in Europe, and in the automotive sector, where the sale of new combustion engine vehicles will be banned from 2035. These constraints require industries to integrate their new technologies into products as quickly as possible. This involves shortening the product development cycle. To reduce these development cycles, one solution is to offload development to suppliers. In this way, customer-supplier relations will become increasingly present. This paper describes a tool-based process to help OEMs and suppliers to exchange simulation models. One of the challenges of this framework is that it must be able to adapt to companies with different vocabulary and operating modes. First, the difficulties were clarified in a workshop with experts from various OEM and supplier companies. This workshop showed that the main problems linked to model exchange between OEMs and suppliers come from the specification and credibility characterization phases of a simulation model. Existing solutions to solves these difficulties are a requirements list, defined by Nasa standard 7009B, the Predictive Capability Maturity Model (PCMM) or the Costa method. However, none of these methods is adapted to the most important criteria of the industry: the design phase, the expected maturity level of the model, and the expertise of the stakeholders. This paper will present two solutions to address each of these issues. These solutions were co-constructed with several simulation experts from companies that are either OEMs or suppliers. The first solution is a set of metadata (MIC core) to help with specification and a checklist composed of 24 requirements. Each requirement belongs to one of the five subsections: the clarity of the specification, the scope of the modeled system, the simulation environment, the model description, and the verification and validation procedure and criteria. These requirements are filtered according to three levels defined above, and filtered according to the MIC field that is filled. The second solution is a credibility assessment questionnaire composed of 21 questions. Responses have been designed to be as interpretable as possible. With, for example, concrete thresholds to be reached or specific actions. These questions are used to calculate a score for 6 distinct categories: model robustness and sensitivity, model uncertainty and margin, expert verification, expert qualitative validation, experimental validation and model use. The main feature of this questionnaire is that some questions are completed by the supplier, and others are completed by the OEM to ensure that the model is used in accordance with the specification. This score is compared with a threshold, which depends on the 3 criteria mentioned above. To assess the feasibility of implementing the approach, a demonstrator was created to support the approach. This article presents the application of the framework using a use case of integrating a fuel cell model into a thermal management model for an electric vehicle. The proposed solutions address the issue of OEM-supplier interaction by improving both the specification process and the credibility assessment of simulation models. Future work will focus on the use of credibility assessment in simulation architectures composed of different models.