Advanced Model Validation and Robust Power Management of Hybrid Green Energy Systems

• Main Authors: Ángel Giancarlo Miranda Canales, 白立文
• Other Authors: Hong, Che-Wun
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/40108489115367779912

博士 === 國立清華大學 === 動力機械工程學系 === 102 === Green energy power sources and storage devices are an ever growing market and research area for vehicles, portable and stationary applications. In green energy vehicles, the power may come from an exclusive main power source or combined with a secondary auxiliary supply. In this research, the main and secondary power source may be composed of a slow dynamics high power throughput energy source such as a fuel cell and a “free” energy source solar cell module. The storage device is chosen to be a lithium-ion battery pack, but may as well be a super-capacitor. This generality is the special characteristic of the proposed power management strategy. The parameter identification is performed by dynamic load conditions and experimental spectroscopy analysis techniques. For the dye sensitized solar cells, a new identification is performed by obtaining the dark-current impedance under different temperatures and then extending this model to the solar cell mode impedance for a reliable representation. The dynamic load method is employed to obtain a high power integrated battery model for the lithium-ion battery pack. This advanced parameter identification technique results in a lightweight but accurate model which can further enhance state of charge Kalman filter based estimators or other advanced techniques. A systematic analysis of an active topology power system with numerical simulations that take into account realistic experimental conditions will also be performed to accurately predict the steady-state effects of two types of power converters on the energy storage and energy source devices; fuel cells, solar cells, olivine batteries, etc. In order to achieve this, it is chosen to (i) employ the Euler-Lagrange (EL) framework to propose new non-ideal models comprising conduction losses (CL) and dead-time (DT) effects of two types of power converters. (ii) Demonstrate the vast improvement of the steady state error reduction for the derived inner current and outer voltage nonlinear passivity based controllers (PBCs) based on the CL+DT models with dynamic simulations. (iii) Provide analytic steady state operation solutions that result from the CL+DT models and their respective PBC controllers which can be employed to predict the current required from the energy source to aid in the design and sizing of hybrid green energy power systems. Without the new CL+DT PBC controllers, the output power is seen to be vastly reduced with respect to the demanded power even with dead-time periods as small as 0.1961 μs if the CL model and ideal model (IM) PBCs are employed. (iv) Modularly unify the system under passivity based nonlinear control laws for a seamless design of the power management system ensuring accurate inner current control tracking during operation. (v) Embed the ability to include power source protection instructions based on advanced model characterizations. With these initiatives, a convenient modularity to adapt to different hybrid power arrangements is proposed and thus, can easily be designed to protect each one of them. The proposed management strategy in this research could be applied to a green power air conditioner, whose load is composed of thermoelectric chips. However, because of the high computational demands of the power converters, the power system cannot be fully simulated alongside. In addition, the time scales of the cabin, DSSCs and LiBS are in the seconds scales, while the power converters time scales are in the microsencond range. Therefore, a novel idea to derive the steady state efficiency of the power converters using fundamental theory from the PBCs will be proposed. The relationship between the cabin dynamics and the environment, as well as the DSSCs and LiBs will be fully simulated with realistic dynamics. A feasibility study will be performed in order to determine scenarios where the solid-state air conditioner may be used and will include guidelines for its success. A MATLAB/Simulink environment will predict the efficiency and performance of the air conditioner in the cabin of a vehicle. Finally, by importing the efficiency relationships from fundamental theory, the electrical efficiency of the system will be designed for the first time.