Enhancing Track Vehicle Design Engineering Through Digital Twins: A Data-Driven Approach

Enhancing Track Vehicle Design Engineering Through Digital Twins: A Data-Driven Approach: Digital Twin technology can significantly improve the engineering product design process, especially when considering ground vehicle applications. Data-driven computer studies can assist engineers and key stakeholders in evaluating performance, durability, and other system design tradeoffs. To enable this process, the availability of relevant, numerically generated, laboratory, and/or field data is required. Proper data use enables the digital exploration of “what-if” scenarios, reducing necessary field testing and allowing for the examination of hard-to-test operating conditions. When considering the Digital Twin toolset, a collection of models and simulations are assembled to supplement virtual testing endeavors. These models include surrogate, CAD/CAE, and others. In this paper, an off-road track vehicle design is reviewed through the fusion of numerical and field data to evaluate future design enhancements. Preliminary results demonstrate that subtle feature upgrades can produce measurable performance gains without compromising listed requirements and specifications. The proposed design framework establishes a methodology for virtual engineering practitioners.