Plenum Performance Predictive and Prescriptive Analytics Using Machine Learning and Meta-Heuristic Optimization 2022-28-0367

Plenum system of automotive vehicles draws atmospheric air using HVAC blower motor through air inlet grille at the bottom of the windshield and uses lower plenum for rainwater drainage after which air flow enters into awning and sugar scoop for evaporator air flow requirement. Awning and sugar scoop component is used in plenum air flow system to ensure the air flow with the required velocity that would meet the performance metric of total pressure drop of plenum air flow system. The optimal design of plenum component is essential since blower motor energy needs to be drawn from the expensive battery pack and any wastage of energy would lead to reduction in range of the Electric Vehicle. The conventional design process utilizes incremental design iteration, engineering intuition and requires significant effort from engineers to meet performance targets within the specified design space. This also may or may not ensure an optimal design.

In this work, a Machine learning tool with extreme gradient boost algorithm is used for development of a robust meta model that is used for quick prediction of awning and sugar scoop performance parameters such as total pressure drop and velocity of air prediction. On this response surface, application of a meta heuristic [1] based global optimization method is demonstrated which uses simplex homological global optimization (SHGO) and differential evolutionary (DE) method for optimum awning and sugar scoop design. Simplex homological global optimization (SHGO) is the concept of homology group growth which is used to solve a global and derivative free optimization problem of arbitrarily high dimensions. Similarly Differential evolution (DE) is a population-based metaheuristic search algorithm [2] that optimizes a problem which can quickly explore very large design spaces. Using these global optimization algorithms, it is observed that the optimized design of the awning and sugar scoop does result in significant reduction of total pressure drop that helps improve the required performance substantially compared to baseline design parameters within the given design space.