This paper presents a systematic design methodology for split hybrid vehicles using a single planetary gearset (PG) as the transmission. The design methodology consists of four steps: 1) analyze clutch locations on the PG and operation modes, 2) generate dynamic models, 3) evaluate drivability (acceleration performance) via forward simulations, and 4) optimize the fuel economy using the dynamic programming technique. The 1-PG split hybrid transmission can have 12 configurations, and each configuration can have four operation modes when three clutches are added. This methodology systematically evaluates all configuration candidates and identifies the optimal design, and we demonstrate how it helps to identify a simplified design based in the output-split configuration used by the Chevy Volt. The simplified design, named the Volt−, has only two of the four operation modes of the original Volt. The Volt− achieves the same fuel economy as the original Volt in the FUDS cycle, and has only slightly reduced drivability and fuel economy in the HWFET cycle. In addition, an improved design based on the input-split configuration used by the Toyota Prius is also identified, named the Prius+, which has one additional mode than the original Prius. The Prius+ outperforms the Prius in both drivability and fuel economy.
- Dynamic Systems and Control Division
Design of Power-Split Hybrid Vehicles With a Single Planetary Gear Available to Purchase
Li, C, Zhang, X, & Peng, H. "Design of Power-Split Hybrid Vehicles With a Single Planetary Gear." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 857-865. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8818
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