Studies from Inner Mongolia University of Technology in the Area of Support Vect or Machines Reported (A Novel Least Squares Support Vector Machine-particle Filt er Algorithm To Estimate the State of Energy of Lithium-ion Battery Under a Wide ...)
Studies from Inner Mongolia University of Technology in the Area of Support Vect or Machines Reported (A Novel Least Squares Support Vector Machine-particle Filt er Algorithm To Estimate the State of Energy of Lithium-ion Battery Under a Wide ...)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on Support Vector Machines are present ed in a new report. According to news reporting from Inner Mongolia, People's Re public of China, by NewsRx journalists, research stated, "The state of energy (S OE) is a key indicator for lithium-ion battery management systems (BMS). Based o n the second-order resistance-capacitance equivalent circuit model and online pa rameter identification using the dynamic weights particle swarm optimization (DW PSO) method, a least-squares support vector machine-particle filter (LSSVM-PF) a lgorithm is proposed to construct a particle filter to estimate the SOE of a lit hium-ion battery, and then transfer the resulting estimation error together with the experimentally measured voltage and current values to a trained LSSVM model , and use the LSSVM model to optimize the SOE estimates obtained by the PF algor ithm twice to improve the accuracy of SOE estimation for lithium-ion batteries."
Key words
Inner Mongolia/People's Republic of Chi na/Asia/Algorithms/Emerging Technologies/Machine Learning/Support Vector Ma chines/Vector Machines/Inner Mongolia University of Technology
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