Method and system for controlling a rechargeable battery

1. A battery management system for a battery that is rechargeable, comprising:

a control system configured to control, in dependence on one or more control system settings, one, two or more of:

current, delivered by or to the battery,

voltage across the battery,

power delivered by or to the battery, and

state of charge of the battery;

a numerical battery model, comprising:

a parametrized electric model describing the battery in terms of an equivalent electric circuit comprising a plurality of electric parameters;

a parametrized thermal model capable of estimating, based on a plurality of thermal parameters, an internal temperature of the battery as a function of current, voltage and/or power delivered by or to the battery; and

an aging model configured to provide:

a remaining expected lifetime function indicating a remaining expected lifetime of the battery;

stress parameters indicative of an instantaneous consumption of the remaining expected lifetime of the battery in dependence on the internal temperature of the battery, and one or more of momentary state of charge, current, voltage and power delivered, wherein at least one stress parameter is defined as a partial derivative of the remaining expected lifetime function; and

updated values for the plurality of electric parameters and/or updated values for the plurality of thermal parameters based on a chronological sequence of internal temperature as obtained from the parametrized thermal model; and

a control system settings update unit configured to adapt the control system settings based on the stress parameters, wherein the control system settings comprise at least one of setpoints, set values, operational limits or operational rules.

2. The battery management system of claim 1 , wherein the control system is further configured to control the internal temperature of the battery through a closed loop control scheme.

3. The battery management system of claim 1 , wherein the control system is based on model predictive control using the parametrized electric and thermal models of the numerical battery model.

4. The battery management system of claim 1 , wherein the equivalent electric circuit of the parametrized electric model comprises a voltage source and a serial resistor connected in series with the voltage source.

5. The battery management system of claim 4 , wherein the equivalent electric circuit of the parametrized electric model comprises an RC element connected in series with the serial resistor, said RC element comprising an RC resistor and an RC capacitor connected in parallel.

6. The battery management system of claim 1 , wherein numeric values for at least one of the plurality of electric parameters depend on the internal temperature of the battery.

7. The battery management system of claim 1 , wherein numeric values for at least one of the plurality of electric parameters depend on instantaneous state of charge (SoC) of the battery.

8. The battery management system of claim 1 , wherein the aging model is configured to be updated to take into account differences between updated model parameters and corresponding observed parameters, wherein the updated model parameters include the updated values for the plurality of electric parameters and the updated values for the plurality of thermal parameters.

9. The battery management system of claim 1 , wherein the remaining expected lifetime function is denoted as L(t, I, V, P, T cell , SoC, DoD), wherein t is time, I is the current delivered by or to the battery, V is the voltage delivered by or to the battery, P is the power delivered by or to the battery, T cell is the internal temperature of the battery, SoC is the state of charge of the battery, and DoD is the depth of discharge of the battery.

10. The battery management system of claim 9 , wherein the at least one stress parameter is defined according to ∂L(t, I, V, P, T cell , SoC, Dod)/∂I, ∂L)t, I, V, P, T cell , SoC, DoD)/∂V, ∂L(t, I, V, P, T cell , SoC, DoD)/∂P, ∂L(t, I, V, P, T cell , SoC, DoD)/∂T cell , ∂L(t, I, V, P, T cell , SoC, DoD)/∂SoC, or ∂L(t, I, V, P, T cell , SoC, DoD)/∂DoD.

11. The battery management system according to of claim 1 , wherein the control system is configured to control, in dependence on the one or more control system settings, exactly one of

current, delivered by or to the battery,

voltage across the battery,

power delivered by or to the battery, and

state of charge of the battery.

12. The battery management system of claim 1 , wherein the numerical battery model is connected to a cloud service, wherein numerical battery models of other batteries are also connected to the cloud service, wherein the numerical battery model is configured to exchange information with the numerical battery models of the other batteries through the cloud service, and is configured to provide the updated values for the electric parameters and/or updated values for the thermal parameters using the information from the numerical battery models of the other batteries.

13. The battery management system of claim 1 , wherein the numerical battery model is a software model and is configured to be run on a computing device.

14. A method for controlling quantities that include one, two or more of a state of charge, a current, a voltage and/or a power delivered by or to a battery, the method comprising:

providing a control system for controlling said quantities in dependence on one or more control system settings under a closed-loop control scheme, wherein the control system settings comprise at least one of setpoints, set values, operational limits or operational rules;

providing a numerical battery model, comprising:

a parametrized electric model describing the battery in terms of an equivalent electric circuit comprising a plurality of electric parameters;

a parametrized thermal model capable of estimating, based on a plurality of thermal parameters, an internal temperature of the battery as a function of current, voltage and/or power delivered by or to the battery; and

an aging model configured to provide:

a remaining expected lifetime function indicating a remaining expected lifetime of the battery;

stress parameters indicative of an instantaneous consumption of the remaining expected lifetime of the battery in dependence on the internal temperature of the battery, and one or more of momentary state of charge, current, voltage and power delivered, wherein at least one of the stress parameters is defined as a partial derivative of the remaining expected lifetime function; and

updated values for the electric parameters and/or updated values for the thermal parameters based on a chronological sequence of internal temperature as obtained from the parametrized thermal model;

determining initial values for the stress parameters and/or the plurality of electric and thermal parameters;

operating the battery under control of a controller with said control system settings;

periodically updating the numerical battery model, in particular the electric and thermal parameters;

selecting updated control system settings based on a given operational range for state of charge, current, voltage, and/or internal temperature of the battery; and

repeating said acts of operating the battery, periodically updating the numerical battery model and selecting updated control system settings.

15. The method of claim 14 , wherein the control system is further configured to control the internal temperature of the battery through the closed-loop control scheme.

16. The method of claim 15 , wherein in said operating the battery, the battery is operated under model predictive control using the parametrized electric and thermal models of the numerical battery model.

17. The method of claim 14 , wherein in said periodically updating the numerical battery model, the numerical battery model is updated using output from the aging model.

18. The method of claim 14 , wherein in said periodically updating the numerical battery model, the numerical battery model is updated using a diagnostic routine.

19. The method of claim 14 , further comprising connecting the numerical battery model to a cloud service, wherein the cloud service is connected to other numerical models of other batteries, wherein in said periodically updating the numerical battery model, the numerical battery model is updated using data obtained from the other batteries connected to the cloud service.

20. The method of claim 14 , further comprising the act of repeatedly updating the aging model to take into account differences between updated model parameters and corresponding observed parameters.

21. The method of claim 14 , wherein the remaining expected lifetime function is denoted as L(t, I, V, P, T cell , SoC, DoD), wherein t is time, I is the current delivered by or to the battery, V is the voltage delivered by or to the battery, P is the power delivered by or to the battery, T cell is the internal temperature of the battery, SoC is the state of charge of the battery, and DoD is the depth of discharge of the battery.

22. The method according to claim 21 , wherein the at least one stress parameter is defined according to ∂L(t, I, V, P, T cell , SoC, Dod)/∂I, ∂L)t, I, V, P, T cell , SoC, DoD)/∂V, ∂L(t, I, V, P, T cell , SoC, DoD)/∂P, ∂L(t, I, V, P, T cell , SoC, DoD)/∂T cell , ∂L(t, I, V, P, T cell , SoC, DoD)/∂SoC, or ∂L(t, I, V, P, T cell , SoC, DoD)/∂DoD.