A predictive energy monitoring system which, during discharge, accounts for changes in available energy remaining as a result of changes in battery environmental temperature, changes in energy used by systems which cycle on and off, and which provides a user “What-if” capability to predict energy availability time remaining by changing systems in use. The present invention also covers the reporting of re-charge completion against multiple re-charge goals. The battery monitoring system includes a non-volatile memory, sensors, a processor that receives inputs from the sensors and receives inputs from a user through a touch screen graphic user interface, the processor then makes calculations responsive to sensor inputs and user inputs, and supplies data to a display for presenting a plurality of screen images representing the results of the calculations.

This application provides a charging time estimation method and apparatus, and a storage medium. The method includes: obtaining a current temperature of a to-be-charged device and a current state of charge (SOC) of the to-be-charged device in a calculation period, and obtaining a required current of the to-be-charged device based on the current temperature and the current state of charge; and determining a charging current of the to-be-charged device; and obtaining a charging time. The method can be applied to a thermal management system of an electric vehicle or an optimization model of an off-line thermal management strategy. In this method, energy consumption of the thermal management system is estimated in a charging process, so as to resolve a problem that the energy consumption of the thermal management system is not considered in the conventional charging time estimation method, to make the estimated charging time more accurate.

This application provides a charging time estimation method and apparatus, and a storage medium. The method includes: obtaining a current temperature of a to-be-charged device and a current state of charge (SOC) of the to-be-charged device in a calculation period, and obtaining a required current of the to-be-charged device based on the current temperature and the current state of charge; and determining a charging current of the to-be-charged device; and obtaining a charging time. The method can be applied to a thermal management system of an electric vehicle or an optimization model of an off-line thermal management strategy. In this method, energy consumption of the thermal management system is estimated in a charging process, so as to resolve a problem that the energy consumption of the thermal management system is not considered in the conventional charging time estimation method, to make the estimated charging time more accurate.

Provided is a device or the like that can improve the accuracy of battery performance evaluation of a rechargeable battery. Parameter values of a rechargeable battery model are identified on the basis of a measurement result of a complex impedance Z of a first rechargeable battery 221. The rechargeable battery model expresses an impedance of an internal resistance of the first rechargeable battery 221 with transfer functions representing IIR and FIR systems, respectively. Performance of a second rechargeable battery 222 is evaluated on the basis of a result of contrast between a voltage response characteristic V(t) that is output from a rechargeable battery 220 as the second rechargeable battery 222 when an impulse current I(t) is input to the second rechargeable battery 222, and a model voltage response characteristic V.sub.model(t) when the impulse current is input to the rechargeable battery model having the parameter values identified.

Provided is a device or the like that can improve the accuracy of battery performance evaluation of a rechargeable battery. Parameter values of a rechargeable battery model are identified on the basis of a measurement result of a complex impedance Z of a first rechargeable battery 221. The rechargeable battery model expresses an impedance of an internal resistance of the first rechargeable battery 221 with transfer functions representing IIR and FIR systems, respectively. Performance of a second rechargeable battery 222 is evaluated on the basis of a result of contrast between a voltage response characteristic V(t) that is output from a rechargeable battery 220 as the second rechargeable battery 222 when an impulse current I(t) is input to the second rechargeable battery 222, and a model voltage response characteristic V.sub.model(t) when the impulse current is input to the rechargeable battery model having the parameter values identified.

Parameters P(n0,n1,n2) of a rechargeable battery model at each of different temperatures T(n1) at each of different degradation degrees D(n2) are determined. The values of the parameters P(n0,n1,n2) of the rechargeable battery model are identified based on a measurement result of a complex impedance Z of a rechargeable battery 220. The rechargeable battery model expresses an impedance of an internal resistance of the rechargeable battery 220 with transfer functions representing the IIR and FIR systems, respectively. Further, a voltage command value Vcmd(t) in the case where a current command value Icmd(t) is input to a rechargeable battery model corresponding to the identifier id(m0), temperature T(m1), and degradation degree D(m2) of the virtual rechargeable battery to be simulated by a simulation battery 20 is calculated, and a voltage V(t) according thereto is applied to the designated apparatus 200 or its load by the simulation battery 20.

A method and/or system configured to select state estimator operation settings based on one or more system inputs; and determine a battery state of a battery, based on sensor measurements associated with the battery, using a state estimator operating under the state estimator operation settings.

A charge control device for charging a battery with electric power supplied from an external power supply includes: an external power supply information acquisition unit that acquires external power supply information including a voltage of the external power supply; a battery information acquisition unit that acquires battery information including a temperature, a voltage, and an electric current of the battery; a power consumption acquisition unit that acquires an amount of electric power supplied from the battery to an auxiliary device as a power consumption amount; and a charge time estimation unit that estimates a charge time of the battery. The charge time estimation unit acquires an initial value of a state of charge of the battery based on the battery information, and estimates the charge time based on the battery temperature, the external power supply information, the power consumption amount, and the initial value of the state of charge.

A charge control device for charging a battery with electric power supplied from an external power supply includes: an external power supply information acquisition unit that acquires external power supply information including a voltage of the external power supply; a battery information acquisition unit that acquires battery information including a temperature, a voltage, and an electric current of the battery; a power consumption acquisition unit that acquires an amount of electric power supplied from the battery to an auxiliary device as a power consumption amount; and a charge time estimation unit that estimates a charge time of the battery. The charge time estimation unit acquires an initial value of a state of charge of the battery based on the battery information, and estimates the charge time based on the battery temperature, the external power supply information, the power consumption amount, and the initial value of the state of charge.

The present disclosure relates to a method and apparatus for determining a state of charge (SOC) of a battery and a battery management system (BMS), so as to resolve a problem such as inaccurate estimation of the SOC. The method includes: acquiring state data of the battery, where the state data comprises current data and voltage data; determining each element parameter value in an equivalent circuit model of the battery based on the equivalent circuit model, error information, battery characteristic data, and the state data by using a recursive least square (RLS) prediction model; and determining an estimated value of the SOC of the battery based on the element parameter value in the equivalent circuit model, the state data, and the battery characteristic data according to a technique of an observer.