Abstract
Hybrid powertrain technologies are successful in the passenger car market and have been actively developed in recent years. Optimal topology selection, component sizing, and controls are required for competitive hybrid vehicles, as multiple goals must be considered simultaneously: fuel efficiency, emissions, performance, and cost. Most of the previous studies explored these three design dimensions separately. In this paper, two novel frameworks combining these three design dimensions together are presented and compared. One approach is nested optimization which searches through the whole design space exhaustively. The second approach is called enhanced iterative optimization, which executes the topology optimization and component sizing alternately. A case study shows that the later method can converge to the global optimal design generated from the nested optimization, and is much more computationally efficient. In addition, we also address a known issue of optimal designs: their sensitivity to parameters, such as varying vehicle weight, which is a concern especially for the design of hybrid buses. Therefore, the iterative optimization process is applied to design a robust multi-mode hybrid electric bus under different loading scenarios as the final design challenge of this paper.
Highlights
Tightening emissions and fuel economy standards are strong driving forces behind vehicle electrification
We propose a novel optimization method, called iterative optimization, which combines the topology optimization and component sizing together
After analysis, winning designs are selected through a launching performance and fuel economy evaluation
Summary
Tightening emissions and fuel economy standards are strong driving forces behind vehicle electrification. Researchers and engineers typically optimize the powertrain designs from three perspectives: control strategy, component sizes, and system topologies. Power-weighted efficiency analysis for rapid sizing (PEARS) is the only known method that can be used to solve multi-mode HEV control problems with demonstrated optimality and can be computed orders of magnitude faster than DP [14]. Silvas et al [28] propose a general framework to generate all possible powertrain structures by solving a constrained logic programming problem Such frameworks can be used for HEVs with any number of PGs and even non-power-split designs, but the computation time can be a challenge. 2 describes process for the (named nested optimization), the topology optimization and component sizing are executed exhaustive search of double-PG hybrid powertrains; in Section 3, the proposed iterative optimization alternately.
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