Motor and Transmission Multiobjective Optimum Design for Tracked Hybrid Electric Vehicles Considering Equivalent Inertia of Track System
| Autor: | Jongseok Lee, Seungjae Min, Kihan Kwon |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
media_common.quotation_subject Energy Engineering and Power Technology Transportation Energy consumption Inertia Multi-objective optimization Traction motor Surrogate model Design objective Control theory Automotive Engineering Torque Electrical and Electronic Engineering media_common Efficient energy use |
| Zdroj: | IEEE Transactions on Transportation Electrification. 7:3110-3123 |
| ISSN: | 2372-2088 |
| Popis: | In the development of hybrid electric vehicles (HEVs), a series hybrid powertrain is mainly utilized in tracked vehicles to reduce energy consumption. In order to achieve high energy efficiency while maintaining the required driving performance, key design parameters of traction systems, such as transmission ratio and motor torque and power, need to be optimized. With the aim of effectively analyzing a complex track system, this article proposes an equivalent inertia model, which collectively represents the motion of each component of the tracked vehicle. The equivalent inertia model showed that the inertial effect was 34.8% higher than when the total mass of the vehicle was considered exclusively. Based on this inertia model, design objectives, such as energy efficiency and driving performance, were defined as quantified functions. Because of the balanced relationships between the objective functions, this study formulated a multiobjective optimization problem that includes motor stack length and transmission gear ratio as design variables. Based on the multiobjective optimization results, a Pareto front was obtained, which illustrates the balanced relationships between the objective functions. Comparing the initial HEV design, the optimum designs can improve energy efficiency and driving performance as a maximum of 13.0% and 2.9%, respectively. |
| Databáze: | OpenAIRE |
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