Automobile Model Digital Engineering Practice

Abstract

With the rapid growth of electrification, intelligence, and customization demands in the automotive industry, parallel development of multiple vehicle models imposes higher requirements on the re-usability, flexibility, and development efficiency of digital engineering models. Based on the practical application of automotive model digital engineering, this paper proposes an overall framework for automotive research and development. By integrating key technologies such as modular hierarchical architecture design, parametric configuration-driven modeling, cross-domain data collaboration management, and automated verification systems, the framework establishes an end-to-end solution spanning requirement analysis, model development, simulation validation, and iterative optimization. Based on a specific vehicle model system development case, this framework achieved a ~50% reduction in system development cycles, ~30% fewer quality issues, and 50% higher model development efficiency. It enables rapid model reuse and facilitates swift derivative design across various power trains (fuel, electric, hybrid) and configurations. The research provides methodological insights for efficient digital engineering systems in automotive industry.