access icon free Novel estimation solution on lithium-ion battery state of charge with current-free detection algorithm

© The Institution of Engineering and Technology
Received 16/08/2018, Accepted 15/10/2018, Revised 30/09/2018, Published 25/10/2018

Lithium-ion battery as an efficient, sustainable, and clean energy for electric vehicles (EVs) and smart devices becomes more popular with the worldwide demand for reduction of greenhouse gas emission. In all kinds of applications, an accurate real-time estimation for state of charge (SOC) of battery is necessary. Some conventional methods usually need to sample both battery currents and voltages. This article presents a novel SOC estimation algorithm without current detection. This algorithm just acquires the port voltages of cell to calculate the open-circuit voltage (OCV) which is related to SOC. By extracting a large number of battery voltages based on a step response, some important parameters that can track battery working process are determined. In order to verify the algorithm feasibility and accuracy, it has been tested on a commercial common field-programmable gate array (FPGA) in different application conditions. The algorithm accuracy is mainly limited by model accuracy and sampling sensor accuracy. The maximum error between ideal SOC and calculated SOC by this algorithm is within 4%, and the mean error is about 0.99%. So, this high-feasibility, accredited accuracy, easy integration, and low-cost solution has bright potential in smarter future.

Inspec keywords: battery powered vehicles; battery management systems; field programmable gate arrays; secondary cells; estimation theory; electric vehicle charging; lithium compounds

Other keywords: battery currents; greenhouse gas emission reduction; commercial common field-programmable gate array; lithium-ion battery state of charge; current detection; electric vehicles; battery voltages; clean energy; smart devices; SOC estimation algorithm; current-free detection algorithm; sustainable energy; battery working process

Subjects: Secondary cells; Logic circuits; Probability theory, stochastic processes, and statistics; Secondary cells; Other topics in statistics

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