In order to significantly expand the BEV market, and to increase the use of lithium-ion batteries in electric grids, there is a need to develop optimal charging strategies to utilize the batteries more efficiently and enable longer life. Advanced battery management systems that can calculate and implement such strategies in real time are expected to play a critical role for this purpose. This article investigates different approaches for determining model-based optimal charging profiles for batteries, and experimentally validates the gain obtained using such profiles. Optimal profiles that maximize the cycle life of the cells are implemented on 16 Ah NMC cells for 30 minutes of charge followed by 5C discharge, and the cycle life is compared to a standard 2C CC-CV charge and 5C discharge. An improvement of more than 100% in cycle life is observed experimentally, for our test conditions on this cell design. This study is the first to experimentally demonstrate that the improved extra knowledge obtained by sophisticated physics-based models results in significant improvements in battery performance when employed in a real time control algorithm.
A resource efficient with low computational overheads SVPWM algorithm for three phase voltage source inverter which is used to supply variable voltage and variable frequency to three phase AC drives is proposed in this paper. Because of its advantages like lower switching losses, higher dcbus utilization SVPWM scheme becomes the preferred PWM technique for various three-phase power converter applications. Conventional SVPWM algorithm involves complex mathematics and requires more hardware resources to implement and takes more time for its execution. The Field Programmable Gate Arrays (FPGAs) offer high computational ability and flexibility due to their parallel execution and reconfigurable hardware. Hence the scheme suggests the implementation of a resource efficient algorithm with low computational overheads for SVPWM generation using FPGA and obtains higher sampling rates with minimal use of hardware resources. Resource utilization of proposed algorithm obtained is 4% for XILINX XC3S500E processor operating at 50 MHz. The output fundamental frequency can be adjusted from 0.1Hz to 1500Hz and PWM switching frequency can be set from 200 to 50 KHz. The adjustable delay time logic for PWM gating signals is also implemented. The proposed algorithm is tested for 3-phase induction motor with VSI and the experimented results are validated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.