Abstract
In order to improve the battery management system performance and enhance the adaptability of the system, a fractional order equivalent circuit model of lithium-ion battery based on electrochemical test was established. The parameters of the fractional order equivalent circuit model are identified by the least squares parameter identification method. The least squares parameter identification method needs to rely on the harsh test conditions of the laboratory, and the parameter identification result is static; it cannot adapt to the characteristics of the lithium battery under dynamic conditions. Taking into account the dynamic changes of lithium batteries, a parameter adaptive online estimation algorithm for fractional equivalent circuit model is proposed. Based on the theory of fractional order calculus and indirect Lyapunov method, the stability and convergence of the estimator are analyzed. Finally, simulation experiments show that this method can continuously estimate the parameters of the fractional order equivalent circuit under UDDS conditions.
Highlights
The battery management system (BMS) is one of the most important technologies in the electric vehicle systems
Mathematical Problems in Engineering the engineering requirements and improving the accuracy of the model is mutually restrictive, and we should try to improve the accuracy of the model as much as possible when the RC network is limited [11, 12]
The fractional equivalent circuit model parameters of the lithium battery are identified by the least squares method under different state of charge (SOC) from hybrid pulse power characteristic (HPPC) test, and the parameter estimation of the whole discharge interval can be obtained
Summary
The battery management system (BMS) is one of the most important technologies in the electric vehicle systems. Some researchers have established fractional equivalent circuits for the electrochemical performance of lithium batteries, but they mainly consider model accuracy and neglect engineering applications. Such as in [15], the author designed a fractional equivalent circuit model containing 2-RC networks, and there are seven parameters in the circuit that need to be identified so that it is difficult to realize online identification. This offline parameter identification method cannot reflect the influence of operating current, state of charge, temperature, and self-discharge on the battery internal characteristics. A simplified fractional order equivalent circuit model for lithium-ion batteries and adaptive online parameter identification method are presented.
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