DE102018204215A1 - Method and system for calculating the battery state of charge - Google Patents

Abstract

A method and system for improving battery state of charge (SOC) estimation using a model based on an adaptive parabolic function including dynamically updating the key parameters of the aging battery compensating behavioral deviation model from the ideal new battery model is provided. The battery model has a parabolic region and a linear region.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

The application claims the benefit of US Provisional Application Serial No. 62 / 483,699, filed April 10, 2017, which is hereby incorporated by reference in its entirety.

TECHNICAL AREA

The present invention relates to a method and a system for estimating or calculating the state of health (SOC) of a battery, and more particularly to a method and a system for calculating the battery SOC using an adaptive, parabolic open circuit voltage versus SOC. model.

BACKGROUND

The amount of fuel remaining in a vehicle fuel tank can be measured directly using various sensor techniques. By contrast, the state of charge (SOC) of a battery can not be measured directly, but must be estimated. Various strategies are used to obtain a correct value of the SOC signal. When the electrical system of a vehicle is active (i.e., charging or discharging), the variation of the SOC signal can be estimated using a Coulomb counting strategy. The Coulomb counting strategy integrates the outgoing (or incoming) current to obtain the amount of electrical charge extracted from (or charged into) the battery.

SUMMARY

One or more embodiments of the invention relate to a method of calculating the state of charge (SOC) of a battery. The method may include determining initial model parameters for an Open Circuit Voltage (OCV) reverse discharge depth (DOD) battery model, obtaining model constants from the model parameters, measuring the voltage of the battery, and calculating the SOC based on the voltage and the battery model include.

One or more further embodiments of the invention relate to a battery monitoring system comprising a battery, a battery sensor connected to the battery, and an energy monitoring system coupled to the battery sensor. The energy monitoring system may be configured to calculate the state of charge (SOC) of the battery using a dynamic open circuit voltage (OCV) reverse discharge depth (DOD) battery model having a parabolic range and a linear range.

One or more further embodiments of the invention relate to a power management system for a vehicle battery comprising an estimation unit and a controller. The estimation unit may be configured to: determine initial model parameters for open circuit voltage (ODV) inverse discharge depth (DOD) battery model, obtain model constants from the model parameters, receive a voltage measured at poles of the vehicle battery, and calculate the state of charge (SOC) the vehicle battery based on the voltage and the battery model. The controller may be configured to transmit control signals to vehicle loads or an alternator based on the SOC of the battery.

list of figures

• 1 FIG. 10 is a simplified block diagram for a battery monitoring system for a vehicle according to one embodiment of the invention. FIG.
• 2 is a typical OCV versus SOC model for estimating the battery SOC.
• 3 is a dynamic, piecewise-defined OCV versus DOD (discharge gap) model with two major areas, parabolic and linear, for estimating the battery SOC according to one or more embodiments of the invention.
• 4a shows an update function for a slope model parameter (S) according to an embodiment of the invention.
• 4b shows an open-circuit voltage-at-full-charge (OCV_FC) model parameter update function according to an embodiment of the invention.
• 5 FIG. 10 is a simplified flowchart illustrating a method 500 of calculating the SOC of the battery according to one or more embodiments of the invention.

DETAILED DESCRIPTION

Embodiments of the invention will now be described in detail, it being understood that the embodiments described herein are merely exemplary of the invention, which may also be embodied by various alternative embodiments. The figures are not necessarily to scale, some of which may be enlarged or reduced in size to illustrate details of particular components. The details of construction and function described and shown herein are not intended to be limiting, but merely representative of those skilled in the art who wish to practice the invention.

1 shows a vehicle 10 with a battery monitoring system (BMS) 12 , one or more batteries 14 includes. The BMS 12 can at least one battery 14 such as a typical 12 volt battery included. The BMS 12 can monitor battery conditions such as the SOC and the state of health (SOH) of the battery.

The battery 14 can be with an alternator or a generator 16 and also with vehicle loads 18 such as an electric motor, an inverter, additional batteries, accessories, and so on. The battery 14 can electrical energy to the vehicle loads 18 feed and electrical energy from the alternator 16 receive. The vehicle loads 18 You can also get electrical energy directly from the alternator 16 receive. The battery 14 can be positive and negative poles 20 exhibit. A battery sensor 22 can directly with one of the battery poles 20 be connected. The battery sensor 22 can measure battery characteristics such as battery voltage, battery current, etc.

The BMS 12 can continue an electric-energy management system 24 that with the battery sensor 22 coupled. The power management system 24 can data signals 26 from the battery sensor 22 which indicate battery conditions and properties. The power management system 24 can be a battery guessing unit 28 and a controller 30 contain. The treasure unit 28 Can the SOC of the battery 14 estimate based on a dynamic model described in detail below. The control device 30 may be a dedicated battery controller such as a battery control module (BCM). Alternatively, the control device 30 a general vehicle controller such as a vehicle system controller / powertrain control module (VSC / PCM). The control device 30 can with the battery 14 , the battery sensor 22 and the treasure unit 28 be coupled and can control signals 32 send based on the SOC of the battery. For example, the control device 30 Control signals to the vehicle loads 18 or the alternator 16 as in 1 shown.

The electrical energy management system 24 can accurately measure the SOC of the battery 14 require. The invention relates to a system, method and model for obtaining an accurate measurement of the battery SOC. The battery SOC calculation method can be applied to lead-acid batteries or the like.

As explained above, the variation of the SOC signal can be estimated using a Coulomb counting strategy that integrates the outgoing (or incoming) current to increase the amount of electrical charge extracted from (or charged into) the battery receive. Coulomb counting has the inherent problem of offset accumulation, which is present in all integration-based algorithms. The offset integration can be minimized with accurate current measurement, but not eliminated. Correction methods are used to compensate for the errors introduced by the current integration. The most common correction method uses a relationship between the SOC and the open circuit voltage (OCV) when the battery is stabilized after a defined rest period. This relationship is usually non-linear, as in 2 can be seen. Vehicle manufacturers often include in their products a set of OCV SOC mappings based on look-up tables (LUTs) for different battery models. It is unlikely that the actual behavior of a particular battery will match the model. This effect gets stronger as the battery ages. An adpative, nonlinear OCV-SOV model is described here.

Although the relationship between the SOC and the OCV is nearly linear in a wide range of SOC, the battery is likely to operate in the upper non-linear segment. Regarding 3 The invention gives a new mathematical model 300 for OCV versus DOD (Discharge Depth) based on a piecewise defined function. Furthermore, a process for dynamically adjusting key parameters of the model for matching the model to the actual behavior of the battery 14 specified. By dynamically updating the key parameters of the model, behavioral variations of an aging battery are compensated.

For convenience, the model can be defined by Depth of Discharge (DOD) instead of SOC. Equation 1 shows the relationship between the DOD and the SOC:
$$DOD\left(\%\right)=100-SOC\left(\%\right)$$

• • OCV_FC: Die Spannung an den Polen 20 der Batterie 14, wenn die Batterie vollständig geladen ist. Eine Stabilisierungsperiode nach dem Laden der Batterie 14 kann abgewartet werden, um einen guten und stabilen Wert von OCV_FC zu erhalten.
• • S: Die Steigung der OCV-versus-DOD-Funktion in dem linearen Bereich. Eine langsame Entladung mit dazwischenliegenden Stabilisierungsperioden muss durchgeführt werden, um diesen Parameter zu erhalten.
• • OCV_FC_EFF: Ein Kreuzungspunkt der OCV-versus-DOD-Funktion in dem linearen Bereich mit der DOD=Nullachse.
• • DODX: Dieser Parameter ist als der Vereinigungspunkt zwischen den parabolischen und linearen Teilen des Modells definiert. Experimentergebnisse zeigen, dass ein empfehlenswerter Wert von DODX zwischen 15% und 30% bleiben sollte. Der Wert von DODX kann jedoch basierend auf der spezifischen Anwendung oder Konfiguration der Batterie nach oben und unten angepasst werden.

As in 3 shown, the proposed model 300 a mixed model containing two main areas: a parabolic area 302 on the upper side and a linear area 304 on the lower side. Four model parameters may be required to form the model and may be obtained through a battery labeling process:

• • OCV_FC: The voltage at the poles 20 the battery 14 when the battery is fully charged. A stabilization period after charging the battery 14 can be waited to get a good and stable value of OCV_FC.
• S: The slope of the OCV versus DOD function in the linear region. A slow discharge with intermediate stabilization periods must be performed to obtain this parameter.
• • OCV_FC_EFF: A crosspoint of the OCV versus DOD function in the linear range with the DOD = zero axis.
• • DODX: This parameter is defined as the union point between the parabolic and linear parts of the model. Experimental results show that a recommended value of DODX should remain between 15% and 30%. However, the value of DODX may be adjusted up and down based on the specific application or configuration of the battery.

The full model expression can be expressed by Equation 2:
$$V\left(DOD\right)=\{\begin{array}{cc}{C}_{2}DO{D}^2+C_{1}DOD+C_0& DOD<DODX\\ C_{4}DOD+C_3& DOD\le DODX\end{array}$$

$${\text{C}}_3=\text{OCV\_FC\_EFF}$$

The model constants in the linear range 304 (C ₃ and C ₄ ) can be obtained directly from the configuration model parameters (Equation 3, 4):
$${\text{C}}_4=\text{S}$$

$${\text{C}}_3=\text{OCV\_FC\_EFF}$$

• • Die Modellspannung kann gleich OCV_FC sein, wenn DOD = 0 (Gleichung 5)
• • Die Funktion kann kontinuierlich sein In DOD = DODX (Gleichung 6)
• • Die Ableitung der Funktion kann kontinuierlich sein in DOD = DODX (Gleichung 7)

$$V\left(0\right)=OCV\text{\_}FC$$

$$V\left(DOD{X}^{+}\right)=V\left(DOD{X}^{-}\right)$$

$$\frac{dV}{dDOD}\left(DOD{X}^{+}\right)=\frac{dV}{dDOD}\left(DOD{X}^{-}\right)$$

To the constants for the parabolic area 302 (C ₀ , C ₁ and C ₂ ), three assumptions can be made:

• • The model voltage can be equal to OCV_FC if DOD = 0 (Equation 5)
• • The function can be continuous In DOD = DODX (Equation 6)
• • The derivative of the function can be continuous in DOD = DODX (Equation 7)

$$V\left(0\right)=OCV\text{\_}FC$$

$$V\left(DOD{X}^{+}\right)=V\left(DOD{X}^{-}\right)$$

$$\frac{dV}{dDOD}\left(DOD{X}^{+}\right)=\frac{dV}{dDOD}\left(DOD{X}^{-}\right)$$

$$C_1=S+2\frac{OCV\text{\_}FC\text{\_}EFF-OCV\text{\_}FC}{DODX}$$

$$C_0=OCV\text{\_}FC$$

The values of the constants in the parabolic domain 302 (C ₀ , C ₁ and C ₂ ) can then be calculated by means of Equations 8, 9 and 10.
$$C_2=\frac{OCV\text{\_}FC-OCV\text{\_}FC\text{\_}eFF}{DOD{X}^2}$$

$${\mathrm{<figure-callout\; id="1"\; label="C"\; filenames="DE102018204215A1\_0015.png"\; state="\{\{state\}\}">C</figure-callout>}}_1=S+2\frac{OCV\text{\_}FC\text{\_}eFF-OCV\text{\_}FC}{DODX}$$

$${\mathrm{<figure-callout\; id="0"\; label="C"\; filenames="DE102018204215A1\_0014.png"\; state="\{\{state\}\}">C</figure-callout>}}_0=OCV\text{\_}FC$$

• • Die Spannung an den Polen der Batterie muss für eine definierte Zeitperiode stabil sein.
• • Der aktuelle Wert von DOD muss über DODX sein.
• • Aus Konsistenzgründen sollte der aktuelle Wert von DOD unter einem Sicherheits-Maximalwert bleiben. Experimentergebnisse zeigen, dass ein empfohlener Wert für diesen Schwellwert bei ungefähr 70% liegen kann. Dieser Schwellwert kann jedoch basierend auf der spezifischen Anwendung oder Konfiguration der Batterie nach oben oder unten angepasst werden.

The proposed algorithm may reset some model parameters if the measured OCV-SOC relationship (eg due to aging) deviates from the internal model. For example, a common effect of battery aging is a variation in slope (S) between OCV and DOD. This effect can be continuously measured and integrated into the above model by updating the values of the model parameters. To update the slope parameter, as in 4a shown first some conditions are met.

• • The voltage at the poles of the battery must be stable for a defined period of time.
• • The current value of DOD must be via DODX.
• • For consistency, the current value of DOD should remain below a safety maximum. Experimental results show that a recommended value for this threshold may be around 70%. However, this threshold may be adjusted up or down based on the specific application or configuration of the battery.

The real voltage of the battery V _meas can be measured between the battery poles. If the three conditions described above are satisfied, a new value (S ') can be calculated by means of equation 11:
$$S\text{'}=\alpha \left(\frac{V_{meas}-OCV\text{\_}FC\text{\_}eFF}{DOD}\right)+\left(1-\alpha \right)S$$

As in 4a and equation 11, the learning rate of the slope may be adjusted with the filter constant α. The greater the value of this constant, the faster the learning response. The value of this constant may also depend on the periodicity of the learning procedure.

• • Die Spannung an den Polen 20 der Batterie 14 ist für eine definierte Zeitperiode stabil
• • Die Batterie Ist vollständig geladen (DOD<3%)

When the battery 14 is fully loaded, the value of the OCV_FC parameter may also be as in 4b be updated. The conditions that the system should meet for updating this parameter are:

• • The voltage at the poles 20 the battery 14 is stable for a defined period of time
• • The battery is fully charged (DOD <3%)

If these conditions are met, the new value of the open circuit voltage for a full (OCV_FC ') charge can be calculated using Equation 12:
$$OCV\text{\_}FC\text{'}=\beta \left(OCV\text{\_}FC-\left(V\left(DOD\right)-V_{meas}\right)\right)+\left(1-\beta \right)OCV\text{\_}FC$$

The filter constant β may be subject to the same restrictions as α

Each time a configuration parameter (S or OCV_FC) is updated, the model constants should be recalculated using equations 3, 4, 8, 9 and 10. The battery SOC value obtained from the direct current integration can be recalibrated using the model described above. In addition, the health status (SOH) of the battery can be derived from the values of the model parameters.

5 is a simplified flowchart showing a procedure 500 for calculating the SOC of the battery 14 according to one or more embodiments of the invention. As shown above, the mathematical model is based 300 for OCV versus DOD used for calculating the SOC of the battery on a piecewise-defined function having two areas, namely a parabolic area 302 on the upper side and a linear area 304 On the bottom side, the key parameters of the model can be dynamically updated to match the behavior of the aging battery 14 equalize. The initial parameters for the model can be found in step 510 be determined. The model parameters may include OGV_FC, S, OGV_FG_EFF and DODX as previously described.

In step 520 For example, the modulus constants for the model expression of Equation 2 can be obtained from the model parameters using, for example, Equations 3, 4, 8, 9, and 10 under the proper conditions and assumptions as described above. The battery sensor 22 then can the battery voltage in step 530 measure, in step 540 can the battery estimation unit 28 estimate or otherwise calculate the discharge depth (DOD) of the battery from the model based on the measured voltage. Once the DOD has been obtained, the SOC of the battery can be determined using Equation 1 in step 550 be calculated. The battery SOC can be used to determine the range of the vehicle, driveline operating modes, and so on.

The process can then go to step 560 progress. In step 560 The model parameters can be updated. For example, the slope parameter S may be updated by equation 11 to obtain S '. Accordingly, the parameter OCV_FC may be updated by means of Equation 12 to obtain OCV_FC '. The updated model parameters S 'and OCV_FC' become S and OCV_FC at the next repetition, respectively. So as soon as the model parameters have been updated, the process may go to step 520 return to calculate new (updated) model constants based on the updated model parameters.

While exemplary embodiments have been described above, it should be understood that the invention is not limited to the embodiments described herein. The foregoing description is intended to be illustrative and not restrictive, with various changes being made to the embodiments described herein without departing from the scope of the invention. In addition, features of various embodiments may be combined to form further embodiments of the invention.

Claims (20)

A method of calculating the state of charge (SOC) of a battery, comprising: Determining initial model parameters for an Open Circuit Voltage (OCV) inverse discharge depth (DOD) battery model having a parabolic region and a linear region, Obtaining model constants for the battery model from the initial model parameters, Measuring the voltage of the battery, and Calculate the SOC based on the voltage and model constant of the battery model. Method according to Claim 1 wherein calculating the SOC based on the voltage and the battery model comprises: estimating the DOD of the battery from the battery model based on the measured voltage of the battery, and calculating the SOC based on the DOD. Method according to Claim 1 which further includes: Updating the initial model parameters to obtain updated model parameters for the battery model and obtaining updated model constants from the updated model parameters. Method according to Claim 1 wherein determining initial model parameters comprises: measuring an open circuit voltage when the battery is fully charged (OCV_FC), obtaining a slope (S) of the battery model in the linear region, determining a crossing point of the linear region with the DOD = zero axis (OGV_FC_EFF) based on the slope, and defining a junction point between the parabolic region and the linear region of the battery model (DODX). Method according to Claim 4 wherein measuring OCV_FC occurs after a stabilization time has elapsed after charging the battery. Method according to Claim 4 wherein S is obtained by performing a slow discharge of the battery with intermediate stabilization periods. Method according to Claim 4 , where the parabolic region for DOD is smaller than DODX and the linear region for DOD is greater than or equal to DODX. Method according to Claim 4 , where DODX can be defined as a value between 15% and 30% of DOD. Method according to Claim 8 wherein the value of DODX is adjusted up or down based on a specific application or configuration of the battery. Battery monitoring system comprising: a battery sensor that can be connected to a battery, and a power management system configured to be coupled to the battery sensor and configured to calculate the state of charge (SOC) of the battery using a dynamic open circuit voltage (OCV) inverse depth discharge (DOD) battery model having a parabolic region and a linear range. Battery monitoring system after Claim 10 wherein the power management system comprises an estimation unit configured to estimate the SOC of the battery based on the battery model, and a control device configured to transmit control signals to vehicle loads or an alternator based on the SOC of the battery. Battery monitoring system after Claim 10 wherein the power management system is configured to: determine initial model parameters for the OCV versus DOD battery model, obtain model constants for the battery model from the model parameters, receive a voltage measured at poles of the battery, and calculate the SOC based on the voltage and the model constant of the battery model. Battery monitoring system after Claim 12 wherein the power management system is further configured to: update the initial model parameters to obtain updated model parameters for the battery model, and obtain updated model constants from the updated model parameters. Battery monitoring system after Claim 12 wherein the SOC is based on the DOD of the battery and the DOD is estimated from the battery model based on the measured voltage of the vehicle battery. Battery monitoring system after Claim 12 wherein the initial model parameters include: an open circuit voltage when the battery is fully charged (OCV_FC), a slope (S) of the battery model in the linear region, a point of intersection of the linear region with the DOD = zero axis (OCV_FC_EFF) based on the slope, and a junction point between the parabolic region and the linear region of the battery model (DODX). Battery monitoring system after Claim 15 , where the parabolic region for DOD is smaller than DODX and the linear region for DOD is greater than or equal to DODX. An energy management system for a vehicle battery, comprising: an estimation unit configured to: Determining initial model parameters for open circuit voltage (OCV) reverse discharge depth (DOD) battery model, Obtaining model constants for the battery model from the initial model parameters, Receiving a voltage measured at the poles of the vehicle battery, and Calculating the state of charge (SOC) based on the voltage and model constant of the battery model, and a controller configured to transmit control signals to vehicle loads or an alternator based on the SOC of the battery. Energy management system after Claim 17 wherein the DOD of the battery is estimated from the battery model based on the measured voltage of the vehicle battery and the SOC calculated based on the DOD. Energy management system after Claim 17 wherein the battery model includes a parabolic region and a linear region. Energy management system after Claim 19 wherein the initial model parameters include: an open circuit voltage when the battery is fully charged (OCV_FC), a slope (S) of the battery model in the linear region, a crossing point of the linear region with the DOD = zero axis (OCV_FC_EFF) based on the slope, and a merge point between the parabolic region and the linear region of the battery model (DODX).

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