Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are crucial technologies for the automotive industry to meet society’s demands for cleaner, more energy efficient transportation. Meeting the need to provide power which sustains HEVs and EVs is an immediate area of concern that research and development within the automotive community must address. Electric batteries and electrical motors are the key components in HEV and EV power generation and transmission, and their performance plays very important role in the overall performance of the modern high efficiency vehicles. Therefore, in this dissertation, we are motivated to study the electric batteries, interior permanent motor (IPM), in the context of modern hybrid electric/electric drive systems, from both multi-physics and system level perspectives. Electrical circuit theory, electromagnetic Finite Element Analysis (FEA), and Computational Fluid Dynamic (CFD) finite volume method will be used primarily in this work. The work has total of five parts, and they are introduced in the following. Firstly, Battery thermal management design is critical in HEV and EV development. Accurate temperature distribution of the battery cells during vehicle operation is required for achieving optimized design. We propose a novel electrical-thermal battery modeling technique that couples a temperature dependent battery circuit model and a physics-based CFD model to meet this need. The electrical circuit model serves as a heat generation mechanism for the CFD model, and the CFD model provides the temperature distribution of the battery cells, which can also impact the heat generation of the electrical battery model. In this part of work, simulation data has been derived from the model respective to electrical performance of the battery as well iv as the temperature distribution simultaneously in consideration of the physical dimensions, material properties, and cooling conditions. The proposed model is validated against a battery model that couples the same electrical model with a known equivalent thermal model. Secondly, we propose an accurate system level Foster network thermal model. The parameters of the model are extracted from step responses of the CFD battery thermal model. The Foster network model and the CFD model give the same results. The Foster network can couple with battery circuit model to form an electric-thermal battery model for system simulation. Thirdly, IPM electric machines are important in high performance drive systems. During normal operations, irreversible demagnetization can occur due to temperature rise and various loading conditions. We investigate the performance of an IPM using 3d time stepping electromagnetic FEA considering magnet’s temperature dependency. Torque, flux linkage, induced voltage, inductance and saliency of the IPM will be studied in details. Finally, we use CFD to predict the non-uniform temperature distribution of the IPM machine and the impact of this distribution on motor performance. Fourthly, we will switch gear to investigate the IPM motor on the system level. A reduced order IPM model is proposed to consider the effect of demagnetization of permanent magnet due to temperature effect. The proposed model is validated by comparing its results to the FEA results. Finally, a HEV is a vehicle that has both conventional mechanical (i.e. internal combustion engine) and electrical propulsion systems. The electrical powertrain is used to work with the conventional powertrain to achieve higher fuel economy and lower emissions. v Computer based modeling and simulation techniques are therefore essential to help reduce the design cost and optimize system performance. Due to the complexity of hybrid vehicles, multidomain modeling ability is preferred for both component modeling and system simulation. We present a HEV library developed using VHDL-AMS.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-3764 |
| Date | 01 January 2013 |
| Creators | Lin, Shao Hua |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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