WO2019206859A1

WO2019206859A1 - Method for estimating the state of charge of an electric battery

Info

Publication number: WO2019206859A1
Application number: PCT/EP2019/060288
Authority: WO
Inventors: Jana KALAWOUN; Michel Mensler
Original assignee: Renault S.A.S; Nissan Motor Co., Ltd.
Priority date: 2018-04-24
Filing date: 2019-04-23
Publication date: 2019-10-31
Also published as: FR3080459B1; FR3080459A1

Abstract

The invention relates to a method for estimating a physical parameter of an electrochemical cell for storing energy, comprising a step (10) of estimating said parameter by an observer of state, modelling the cell as a voltage source and n parallel RC circuits connected in series, where n is an integer greater than or equal to 1. According to the invention, the method comprises, if the estimated value of the parameter is in a predefined range, a step (12) of correcting said estimation including taking account in the observer of a voltage corrective term, said term corresponding to at least one (n+1)^th parallel RC circuit connected in series with the voltage source.

Description

METHOD FOR ESTIMATING A CHARGE STATE OF A BATTERY

ELECTRIC

The invention relates to a method for estimating a state of charge of an electric battery. Such a method is fully justified in a motor vehicle comprising such an electric battery, and for which the state of charge of said battery will notably result in a driving autonomy.

Even if the state of charge estimation methods of a battery currently in use generally give good results over a wide range of states of charge of the battery, they remain rather imprecise, for example to estimate the states of charge of the battery. low charge. This poor estimate is mainly due to a different behavior of the battery at these low states of charge, compared to the behavior of the latter at higher charge states.

The application FR3029315 discloses a method for estimating the state of charge of an electric battery cell, by means of a Kalman filter modeling said cell as a voltage source and n parallel RC circuits, connected in series. However, the disadvantage of such a method is that it requires a high CPU load (English Central Processing Unit) and an extended memory space.

A method according to the invention makes it possible to accurately estimate the state of charge of a battery cell, including a low state of charge of said cell, by overcoming the drawbacks noted in the state of the art. .

It should be noted that the terms "state of charge" and "SOC" (State of Charge) are equivalent.

The subject of the invention is a method for estimating a physical parameter of an electrochemical energy storage cell comprising a step of estimating said parameter by a state observer modeling the cell as a source of voltage. and n series connected parallel RC circuits, where n is an integer greater than or equal to 1. The main technical characteristic of a method according to the invention is that it comprises a step of correcting said estimate including taking into account in the observer a corrective term in voltage, said term corresponding to at least one (n + l) ^th parallel RC circuit connected in series with the voltage source. As a reminder, an RC circuit is a circuit comprising a resistor R and a capacitor C connected in parallel. If the parameter to be estimated is found in the predefined range of values, for which the estimate of said parameter may be critical or erroneous, an estimation method according to the invention proposes to introduce a corrective term to this estimate, which is added to the value determined by the observer. In other words, this corrective term does not interfere directly with the observer's calculations, but rather is added upstream of them, independently. An estimation method according to the invention can thus consider n + 1 RC circuits, n + 2 RC circuits, etc. The number of RC circuits to be considered, will depend on the predefined range of values in which finds the physical parameter, and the nature of the physical parameter. By way of example, this physical parameter may be a state of charge of an electrochemical energy storage cell. An estimation method according to the invention is particularly but not exclusively adapted to the estimation of a state of charge of an electric battery of a motor vehicle, in order to know the mileage autonomy of said vehicle at each moment of rolling of it.

Advantageously, the physical parameter is a state of charge of the battery.

Preferably, the state observer is a Kalman filter.

For example, the predefined range is 0% to 20%. Indeed, the estimation of the state of charge of an electrochemical cell can pose some problems when this state of charge is low, because the physical and electro-chemical phenomena involved are different from those encountered for values. higher.

Advantageously, if the estimated value of the state of charge is in the predefined range, the correction step comprises:

A step of calculating the at least one corrective term in voltage, - A step of adding said corrective term to the voltage taken into account by the observer to perform the estimation;

- A step of reestimating the state of charge by the observer from this corrected voltage.

Preferably, the SOC estimation step is performed by means of Ampere-hour counting.

Preferably, when the observer is a Kalman filter, the corrective term is given by the formula:

Or

U _{RC (n +} 1) (t): voltage of the (n + l) ^th RC couple

R _{(n + i)} : Resistance of the (n + l) ^th RC couple

C _{(n + i)} : Capacitance of the (n + l) ^th RC couple

T _s : sampling time

I (t): current intensity at time t

This corrective term is general, and corresponds to the case where the Kalman filter contains n RC circuits.

Advantageously, the corrected voltage is given by the formula:

U _RQ (t) is the voltage of the impedance RC, predicted by the Kalman filter U _{RC (n + i)} (t) is the corrective term,

OCV (SOC (t)) is the open circuit voltage of the cell (English Open Circuit Voltage)

Ro (t) is the resistance

I (t) is the intensity of the current at time t

Advantageously, an estimation method according to the invention is implemented by means of a computer embedded in a vehicle and having a suitable software, said computer being associated with a screen capable of displaying a value representative of the estimated parameter. In this way, if the parameter to be estimated was for example a state of charge of an electric battery of a vehicle, the driver would be constantly informed of the value of this parameter, either by a direct display of the value of this parameter, or by a display of another parameter which may for example be the remaining kilometer of the vehicle.

An estimation method according to the invention has the advantage of being easy and quick to implement, by using a Kalman filter for all the values of the parameter to be estimated, and by using said Kalman filter to be a correction term has been added for ranges of critical values of said parameter. In other words, such a method is safe, reliable and reproducible regardless of the value of the parameter to be estimated.

The following is a detailed description of a preferred embodiment of an estimation method according to the invention, with reference to the following figures:

FIG. 1A is a diagram illustrating an example of comparison between a reference variation and an estimated variation by means of a Kalman filter comprising a resistance and a torque RC, of the state of charge of an electrochemical cell. an electric battery over time,

FIG. 1B is a diagram illustrating an example of the error variation on the estimation of the state of charge over time with a Kalman filter comprising a resistor and a torque RC,

FIG. 2 is a diagram illustrating an example of the comparison between a reference variation and an estimated variation of the voltage of the impedance U _RCi over time,

FIG. 3 is a diagram illustrating an example of the error variation on the estimation of the voltage of the impedance U RCI over time with a method of the state of the art,

FIG. 4 is a view of a model of behavior of the cell comprising a pair RC, a resistor Ro and a source of voltage, this model being used by the Kalman filter to estimate the state of charge.

FIG. 5 is a simplified diagram illustrating an estimation method according to the invention when the state of charge is in a predefined range, FIG. 6 is a simplified logic diagram illustrating the main steps of an estimation method according to the invention, and based on a Kalman filter as an observer,

FIG. 7 is a detailed flowchart illustrating the main steps of an estimation method according to the invention,

FIG. 8 is a diagram illustrating an example of comparison between a reference variation and a variation estimated by means of a method according to the invention, of the state of charge of an electro-chemical cell of an electric battery. in the course of time,

FIG. 9 is a diagram illustrating an example of the error variation on the estimation of the state of charge over time with a method according to the invention,

FIG. 10 is a diagram illustrating an example of the comparison between a reference variation and a variation estimated by means of a method of the state of the art and a method according to the invention, of the voltage of the impedance U _RC over time,

As a reminder, with reference to FIG. 4, a Kalman filter can be with two states, the state of charge and the impedance voltage U _RC , and with a single observation, the voltage of the battery. This model is based on the following equations:

SOC (t)

¾ci (- 1

wire (

U (t) = OC

SOC (t): state of charge

T _s : Sampling time

I (t): the intensity of current at time t

Capacity: cell capacity

U _R ci (t): voltage of the impedance RC at time t

Ri: resistance of the RC couple

Ci: capacitance of the RC couple OCV (SOC (t)): Vacuum voltage of the cell (English Open Circuit Voltage)

Ro: Resistance of the cell

U (t): measured voltage of the cell

The problem is that the Kalman filter can not integrate the strong changes in the state of charge of an electrochemical cell, when this state of charge is in a predefined range of values and corresponding to a low state of charge.

The voltage U _R c can be calculated from the following formula:

Where OCV is the open circuit voltage, Z is the impedance and I is the current intensity.

Referring to FIG. 1A, if a complete discharge of an electrochemical cell of a constant current electric battery is considered, an existing method, without the introduction of the corrective term, and making it possible to estimate the state of charge over time of said cell, gives satisfactory results for medium or high load states, and gives approximate results when said states of charge are low, that is to say when they are by example between 0 and 15%. Indeed the reference curve 1 and the curve 2 representative of the estimation of the state of charge are confused up to 8000s-10000s, then diverge beyond to reach 4% -5%.

Indeed, referring to FIG. 1B, the error made on the estimation of the state of charge remains low until about 8000s-10000s (error less than 3%), time range for which the state of cell load is high or medium, and grows quite significantly above 10000s to exceed 4%, that is to say when its state of charge is low.

These observations are due to the fact that existing methods for estimating the state of charge of an electrochemical cell are based on a Kalman filter and that the cell behaves differently when its state of charge is low. which is not modeled in the Kalman filter equations. With reference to FIG. 2, the variation of the voltage across the impedance over time has two phases: one which is linear and stable corresponding to the high or medium charge states, and the other which is uneven and corresponds to the low states of charge. As well as the reference curve 3 and the representative curve 4 of the estimate of the voltage U _R c are confounded up to 14000s-15000s, as the said curves 3, 4 diverge significantly beyond this period, translating a real difficulty to estimate the voltage U RC at the terminals of the electrochemical cell for the low states of charge.

Referring to FIG. 3, the error made on the estimation of the URC voltage at the terminals of the electrochemical cell, with an estimation method using a Kalman filter, is practically zero up to 14000s-15000s , corresponding to high or medium charge states, and increases abruptly beyond 15000s, corresponding to the low charge states of the electrochemical cell.

With reference to FIG. 5, in order to enable accurate estimation of the state of charge of an electrochemical cell when this state of charge is included in a predefined range that can for example be between 0 and 15% ( corresponding to low charge states), an estimation method according to the invention implements at least one correction term which is added to the Kalman filter.

In this way, if the Kalman filter models the cell as a voltage source and n parallel circuits RC parallel connected in series, an estimation method according to the invention implements a step of correction of said estimate by the addition of a voltage correction term calculated by considering at least n + 1 parallel RC circuits connected in series with the voltage source, if the estimated value of the parameter is within the predefined range. It should be noted that a corrective term is added to the observer's innovation calculation to model a particular behavior of the cell that is not modeled in the observer's equations.

It should be noted that the logic diagram of FIG. 7 is valid for a given observer, while the logic diagram of FIG. 6 is focused on a Kalman filter type observer. For the rest of the description, the observer will be considered to be a Kalman filter. This is an illustrative and non-limiting example of an observer concerned by a method according to the invention.

Referring to FIGS. 6 and 7, a method for estimating the state of charge of an electrochemical cell according to the invention comprises the following steps:

A step 10 of estimating the SOC by means of an Ampere hour count,

A step 11 of estimating the voltage at the terminals of the electrochemical cell,

A step 12 of calculating at least one corrective term that can be added to the Kalman filter,

A comparison step 13 of the value of the SOC estimated by the Kalman filter, with a predefined range of values,

> If the value of the SOC estimated by the Kalman filter is not included in a range of values, for example not included in a range between 0 and 15%, or greater than the threshold value of 15%, the value of the SOC estimated by the Kalman filter will be considered satisfactory,

> If the value of the SOC estimated by the Kalman filter is included in a range of values or is less than a threshold value, for example, included in a range between 0 and 15%, or lower than the threshold value of 15% , the corrective term will then be added to the Kalman filter.

Referring to FIG. 6, the estimation of the state of charge of the electrochemical cell by means of the Kalman filter at time t is carried out on the basis of the following formulas:

T _s xl (t)

SOC (t) = SOC (t - 1) +

Capacity (Eq. 1)

Psocit) - Psocit- 1) + Ql PuRCl it) - PuRCl iP ^~ 1) + 2

OR Psoc ( ^: variance of SOC at time t

^P _{[/ RCI} ( ^: variance of U _R c at time t

Qi: Variance modeling the error of equation 1

Q ₂ : Variance modeling the error of equation 2

The calculation of the corrective term is made from the following formula:

OR

U _R c ₂ (t): voltage of the impedance voltage RC ₂

R _2: Resistance 2 ^nd torque RC

C _2: Capacitance of ^2nd torque RC

T _s : sampling time

I (t): current intensity at time t

Such a method is controlled by a computer embedded in the vehicle. It is iterative during a rolling phase of the vehicle, in order to provide real-time and permanent information to the driver on the state of charge of his battery, or on the remaining mileage of his vehicle, said autonomy being linked to this state of charge.

Referring to FIG. 8, it can be seen that the estimation of the SOC when a corrective term has been added to the Kalman filter is satisfactory for the low values of SOC, as evidenced by the good overlay of the portion of the SOC. the curve 5 representative of the estimated value of said SOC taking into account the corrective term, and the corresponding reference curve 1.

Indeed, referring to Figure 9, the error made on the estimation of the state of charge of the electrochemical cell becomes low again beyond 16000s, corresponding to a low charge state. This improvement is essentially due to the addition of the corrective term to the Kalman filter.

Referring to FIG. 10, the variation of the voltage U _R c at the terminals of the electrochemical cell over time has two phases: one that is linear and stable corresponding to the high or medium charge states, and the other which is uneven and which corresponds to the weak states of charge. Both the reference curve 3 and the representative curve 4 of the estimation of the URC voltage are merged up to 14000s-15000s, as the said curves 3, 4 diverge significantly beyond this period, translating a real difficulty to estimate the voltage U RC at the electrochemical cell terminals for the low states of charge . When the correction term is added to the Kalman filter, the estimate of the value of the voltage URC is satisfactory for the low values of SOC, as evidenced by the good superposition of the portion of the curve 6 representative of the estimated value. said URC voltage, taking into account the corrective term, and the corresponding reference curve.

Claims

1. A method for estimating a physical parameter of an electrochemical energy storage cell comprising a step of estimating (10) said parameter by a state observer modeling the cell as a voltage source and n parallel RC circuits connected in series, where n is an integer greater than or equal to 1, characterized in that it comprises, if the estimated value of the parameter is in a predefined range, a step of correction (12) of said estimate including the taking into account in the observer a voltage correction term, said term corresponding to at least one (n + 1) ^th parallel RC circuit connected in series with the voltage source.

2. Estimation method according to claim 1, characterized in that the physical parameter is a state of charge of the battery.

3. Estimation method according to claim 2, characterized in that the state observer is a Kalman filter.

4. Estimation method according to any one of claims 2 or

3, characterized in that the predefined range is between 0% and 20%.

5. Estimation method according to any one of claims 2 to

4, characterized in that, if the estimated value of the state of charge is in the predefined range, the correction step (12) comprises:

A step of calculating the at least one corrective term in voltage,

- A step of adding said corrective term to the voltage taken into account by the observer to perform the estimation;

6. Estimation method according to claim 5, characterized in that the step of estimating the state of charge is performed by means of an ampere hour count.

7. Estimation method according to any one of claims 2 to 6, characterized in that when the observer is a Kalman filter, the corrective term is given by the formula:

Or

U RC (n ₊ 1) (t): voltage of the (n + l) ^th RC couple

R _{(n + i)} : Resistance of the (n + l) ^th RC couple

C _{(n + i)} : Capacitance of the (n + l) ^th RC couple

T _s : sampling time

I (t): current intensity at time t

8. Estimation method according to claim 7, characterized in that the corrected voltage is given by the formula:

- ff ₀ (t) x / (t)

Or

U RC _Î (t) is the voltage of the impedance RC, predicted by the Kalman filter U _{RC (n + i)} (t) is the corrective term,

OCV (SOC (t)) is the empty voltage of the cell (English Open Circuit

Voltage)

Ro (t) is the resistance

I (t) is the intensity of the current at time t

9. Estimation method according to any one of claims 1 to 8, characterized in that it is implemented by means of a computer embedded in a vehicle and having a suitable software, and in that said computer is associated with a screen capable of displaying a value representative of the estimated parameter.