Aiming at the complex coupling relationship between the electrical and thermal characteristics of the battery

the influence of temperature on the power performance of the battery and the complex correlation between the state of charge (SOC)

the state of temperature (SOT) and state of power (SOP)

this paper proposes a multistate cooperative estimation method of the battery modules that considers the electrical and thermal coupling characteristics. First

the coupling relationship between the electrical and thermal characteristics of the battery is analyzed. The fractional order equivalent circuit model and the lumped parameter two-state thermal model are combined to construct the electric-thermal model of the battery modules. Second

to address the problem that the electro-thermal coupling relationship requires accurate state of charge and state of temperature to maintain

the adaptive extended Kalman filter (AEKF)

is used to realize the state of charge and state of temperature estimation of the battery modules. Finally

the correlation characteristics between different states are analyzed. The state of charge and state of temperature of the battery are introduced into the estimation of state of power under multiple constraints to realize the collaborative estimation of multiple states of the battery modules and improve the accuracy of the battery state estimation. The results show that the method proposed in this paper can quickly converge to the true value with an initial error of 20% in the charge state

and the root mean square error is within 0.52%

and the core and surface temperature estimation errors are within 0.36 ℃ and 0.31 ℃

respectively. At 40 ℃

the core temperature constraint works and the peak power estimation results are significantly reduced

which provides the real-time safety monitoring of power batteries.