Modified Computational Design Synthesis Using Simulation-Based Evaluation and Constraint Consistency for Vehicle Powertrain Systems

The combinatorial nature of powertrain system design problems challenges system engineers as powertrain components can be interconnected, sized, and controlled in numerous ways. Hence, finding promising candidates considering, e.g., fuel economy, drivability, and complexity requires a systematic approach. A dedicated and novel framework for computational design synthesis is, therefore, presented in this paper. The underlying aim of this framework is to enable full-automated powertrain system optimization over multiple system layers, including topology selection, component sizing, and optimal control, and follows the principles of platform-based design. Based on a library of components, system topologies are automatically generated by solving a constraint satisfaction problem. Meanwhile, constraints originating from customers' requirements, application-specific design rules, and physical laws are respected. Furthermore, the topology generation can be applied to hierarchical decomposed systems on multiple system levels in order to reach the full potential of system design. Using a relevant automotive use case, it is demonstrated that possible topologies for powertrains equipped with a complex continuously variable transmission are automatically synthesized. Next, simulation-based evaluation (automated physical modeling and filtering) of these candidates by this framework results in a set of feasible topologies, satisfying the required functionality and physical constructibility. Along with this topology evaluation phase, a control-actuation scheme and an initial set of feasible component parameters are obtained that are required for full-automated multilayer optimization, which is seen as the next novel future step. The presented framework leads to novel and innovative powertrain and transmission designs with a total amount of 635 feasible transmission topologies based on maximum 13 components, whereas the overall time required to generate and evaluate all initial possible candidates (2.5 ·10²⁷) is relatively short, i.e., 5.5 and 20 h, respectively.