![]() Power electronics, serving as power conversion mechanisms, are key linking subsystems consisting of electronic devices, electro-mechanical units, energy storage, etc. Although many systems are becoming predominantly electrical dependent, an integrated multi-physics energy approach creates additional avenues to higher power density, system efficiency, and reliability. Modern large energy systems such as electricity grids and electrified transportation encounter increasing processed power in multi-physics domains, such as electrical, mechanical, thermal, and chemical. Upon evaluating the system performance reveals that the redesigned control system is capable of operating the PV panel at its maximum power point under different atmospheric and load conditions and can provide a constant DC voltage to the critical load while charging the battery with the extra power from the panel. The controllers for the PV system are redesigned using these models, and the closed-loop system is simulated with variable temperature, irradiation and load levels. This requires the use of an alternate technique based on the use of simulated input/output data to determine an operating point around which a linear system model is derivable. It is also problematic that one cannot use conventional linearization methods to model the system and design the controller because the system contains large nonlinearities caused by elements such as DC/DC switching converters driven by pulse width modulation (PWM). This behavior is due to the parameters and dynamics of real circuit elements not taken into account by the design. This system reveals some unexpected behavior when it is subjected to certain irradiation, temperature and load changes. A theoretically designed system based on standard methods found in the literature is modeled and simulated numerically. MPPT Simulation MATLAB a b s t r a c t This paper focuses on the utilization of numerical modeling and simulation to improve the performance of a theoretically designed stand-alone photovoltaic (PV) system with constant DC voltage. Results from simulations and measurements of lithium-ion battery packs show that the proposed battery model behaves well and interacts appropriately with other subcomponents of the vehicle simulator. Validation of the Simulink model is through a battery testing apparatus with a hardware-in-the-loop driving schedule that cycles real batteries. The lithium-ion battery model is programmed into a MATLAB/Simulink environment and used as a power source within an existing comprehensive dynamic vehicle simulator. In particular, data sets for a Panasonic CGR18650 Li-ion battery cell are tabulated for direct use. One focus of the paper is presenting a systematic and generic methodology for parameter extraction as well as obtaining SOC factors through reasonable test work when evaluating any given lithium-ion, nickel-metal hydride, or lead-acid battery cell. Thermal modeling predicting real-time battery temperature is introduced. ![]() The SOC captures effects from discharge and charge rate, temperature, and battery cycling. The model parameters include open circuit voltage, series resistance, and equivalent RC circuits, with nonlinear dependence on battery SOC. An electric battery model utilizing multiple time constants, to address ranges of seconds, minutes, and hours, is developed. ![]() Simulation of electric vehicles over driving schedules within a fully dynamic electric vehicle simulator requires battery models capable of accurately and quickly predicting state of charge (SOC), I-V characteristics, and dynamic behavior of various battery types.
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