- Book Name: Battery Management System BMS for Lithium Ion Batteries
- Pages: 98
- Size: 47 MB
Battery Management System for Lithium Ion Batteries PDF
Contents of Battery Management System for Lithium Ion Batteries PDF
- State of the Art
- ISR-Battery Management System
- Battery Modeling
- BMS Experimental Results
- Conclusion and future work
- BMS Schematics
- Firmware File Structure
- BMS-ISR Graphical User Interface (GUI)
- Winston Battery Datasheet
Preface of Battery Management System for Lithium Ion Batteries PDF
The Electric Vehicle (EV) is already on the roadmap of every important car manufacturer and is seen as the solution to a more sustainable transport system, contributing to a reduction of the Greenhouse Gas Emissions. The Energy Storage System (ESS) is a key component for EVs. This includes the battery and all the management and monitoring systems that compose the Battery Management System (BMS).
Those batteries have very demanding requirements regarding safety, power density (acceleration), energy density (autonomy), high efficiency, deep discharge cycles or low self-discharge rates to name a few. From the available chemistries for the construction of EV batteries the Lithium-Iron-Phosphate (LiFePO4), Lithium-Yttrium-Iron-Phosphate (LiYFePO4) or Lithium-Manganate (LiMn2O4) are the most safe and long lasting and because of that they are studied at the ISR-UC.
The energy monitoring and management systems for EVs use proprietary State of Charge (SOC) algorithms that do not allow their easy use or improvement. For this reason was developed at the ISR-UC a new BMS with an open and flexible architecture allowing the implementation of new SOC estimation algorithms, the ISR-BMS.
During this dissertation, a commercial BMS was installed and tested on a Lithium-Ion battery pack that powers one of the electric platforms available at the ISR-UC. A new platform was completely re-instrumented during the course of this project and required a new ESS to replace their original lead acid batteries, which became end of life. The SOC of the battery is a vital information to the EV user.
It can be displayed as the percentage of full charge capacity that is still available from the battery or be used to estimate the vehicle range based on additional information from previous driving cycles. However, it can not be measured directly from the battery and have a strong dependence with the temperature and the operating conditions.
Several SOC estimation techniques are mentioned on the literature, that require cell models with different complexity and computer process requirements. In this work an Equivalent Electrical Circuit (EEC) model was adopted, with its parameters estimated based on experimental data collected through cell testing at different temperatures and charge/discharge current profiles.
After installation of the ISR-BMS on the platform, on-road drive tests were performed to acquire relevant information and validate the accuracy of collected measurements.
Battery management system for lithium ion batteries pdf.