Research And Design On The Lithium-ion Battery Management System Of Unmanned Surface Vehicle

As a new type of intelligent marine observing platform, the unmanned surfacevehicle (USV) has become a research hotspot in the field of ocean observation. Asthe core management and protection unit of lithium-ion batteries in the electricpropulsion USV, battery management system (BMS) is essential to improve thesafety, reliability and intelligence of the whole system. BMS has been one of thecore technologies of a high-performance USV. This paper includes two parts,estimating the state of charge (SOC) of the lithium-ion battery and design andimplementation of the BMS.By analyzing the characteristics of lithium-ion and relevant factors, this paperbuilds the equivalent circuit model, gets state-space equations and vertifies theveracity of the model. Based on the research above, this paper analyzes anddiscusses the extended Kalman filter algorithm and the adaptive Kalman filteralgorithm to estimate SOC of the lithium-ion battery. Through simulation, it isproved the adaptive Kalman filter has better accuracy and robustness than theextended Kalman filter algorithm. It is difficult for BMS to estimate the SOC of thelithium-ion battery accurately online, which is important for USV to have anefficient use of energy and to give rational route planning. Therefore this paperintroduces a feasible and relatively accurate method which combines the extendedKalman filter algorithm, open-circuit voltage method with the ampere-hourintegration approach and takes the effect of temperature, rate of charging ordischarging current into consideration.And then this paper introduces the design of BMS in the USV. As to thehardware, this paper uses cost-effective STM32F103RBT6as the MCU, theintegrated chip ISL9208for data acquisition. It has temperature sensors, currentsensors, the CAN and serial communication modules as the units of BMS. For thesoftware, it includes the design of the basic data collection, protection, SOCestimation, equalization of battery pack and the communication between the BMSand USV. Meanwhile, the paper analyzes the results of BMS experiment, whichshows that BMS is able to capture single battery voltage, temperature, charging ordischarging current accurately and achieve a relatively accurate estimation of theSOC. The BMS also has the functions of balancing and protecting the battery packwhen the voltage or current of the battery pack is to be unusual.