CN105911480A - Power battery SOC estimation method - Google Patents
Power battery SOC estimation method Download PDFInfo
- Publication number
- CN105911480A CN105911480A CN201610252852.9A CN201610252852A CN105911480A CN 105911480 A CN105911480 A CN 105911480A CN 201610252852 A CN201610252852 A CN 201610252852A CN 105911480 A CN105911480 A CN 105911480A
- Authority
- CN
- China
- Prior art keywords
- equation
- battery
- electrokinetic cell
- power battery
- soc
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
Abstract
The invention belongs to the field of electric automobile power battery management, and relates to a power battery SOC estimation method. The power battery SOC estimation method adopts the following steps that a power battery RC equivalent circuit model is established so that the state space equation of a power battery is obtained; the observation matrix of a system is obtained according to the state space equation of the power battery model, and the observability of the system is judged; an improved signum function is used as a switching function and a sliding-mode observer is designed; the error dynamic equation of the battery is obtained by utilizing the state space equation of the battery and the designed sliding-mode observer equation; and an appropriate Lyapunov function is selected, and the final SOC estimation equation of the power battery is obtained through the stability conditions. The modeling accuracy of the power battery is enhanced, system buffeting can be greatly reduced by the designed sliding-mode observer and external interference and modeling error can be greatly compensated.
Description
Technical field
The present invention relates to electric automobile power battery management domain, particularly relate to a kind of electrokinetic cell SOC method of estimation.
Background technology
Along with the fast development of modern industrial technology and being continuously increased of Global Auto quantity, coal, oil etc. are traditional
Non-renewable energy resources have been difficult to meet human wants, and the conventional fossil resource constantly consumed brings the most broken to environment
Bad.In recent years, along with environmental protection conceptual understanding is deepened continuously by people, electric automobile earns widespread respect.As electric automobile
The electrokinetic cell of critical component and main energy sources becomes the core of research.In order to obtain the available energy content of battery, optimize electricity
The management system in pond, extends the life-span of battery, needs accurately to monitor the running status of battery.Various running statuses at battery
In, battery charge state (State of Charge is called for short SOC) is mostly important.
SOC is very important parameter in cell management system of electric automobile, but can not directly record electricity in actual application
The SOC in pond, SOC to be estimated, it is necessary to indirectly obtained by other physical quantitys and parameter.The most conventional SOC method of estimation has: peace
Time metric method, open-circuit voltage method, neural network, Kalman filtering method, Design of Observer method etc..The mensuration ultimate principle of ampere-hour meter
It is that electric current is carried out temporal integration, the cumulative error of SOC can be caused for a long time；Open-circuit voltage method needs battery in use
Long-time standing, it is impossible to estimate for the online SOC of battery, actual application seldom used；Neural network needs a large amount of
Sample training data, calculate process complicated；Kalman filtering method is the Processing Algorithm of optimization autoregression data, but should
The application of method need to rely on exactly accurate battery equivalent model, and process is loaded down with trivial details；Sliding mode observer method is simpler by it
Single method and stronger robustness, be widely applied.But, traditional sliding mode observer is using signum function as cutting
, there is obvious chattering phenomenon in exchange the letters number, have impact on the precision that electrokinetic cell SOC estimates.
Summary of the invention
The defect existed for above-mentioned SOC method of estimation, the present invention proposes a kind of based on the sliding mode observer improved
Electrokinetic cell SOC method of estimation, weakens chattering phenomenon, improves the estimated accuracy of electrokinetic cell SOC.
The invention discloses a kind of electrokinetic cell SOC method of estimation, comprise the following specific steps that.
Set up electrokinetic cell RC equivalent-circuit model, obtain electrokinetic cell state-space model:
。
Wherein,WithRepresent system external disturbance and modeling error.
It is reduced to
。
Wherein
。
For the observability of proof system, write out observing matrix as follows:
。
Wherein
。
Obviously,Always full rank, so battery system is observable, can be observed device design.
The Design of Sliding Mode Observer improved is as follows:
。
Wherein,,WithIt is respectively,WithEstimated value,,WithObserve for sliding formwork
Device gain, and,。
State equation error is defined as follows:,,。
Switching function is the signum function improved
。
Wherein,For positive number.
Thus obtaining battery error dynamical equation is
。
For the stability of proof system, choosing Lyapunov function is:
。
This Lyapunov function derivation can be obtained:
。
Wherein,。
Thus can obtain:
。
By above-mentioned condition, obtain battery SOC error equation as follows:
。
In like manner, for proving the convergence of SOC error, choosing Lyapunov function is:
。
RightDerivation obtains
。
Wherein,。
Thus obtain:
。
Obtained by above-mentioned condition:
。
The above analysis can obtain,, meet stability condition.
Accompanying drawing explanation
Fig. 1 is electrokinetic cell RC equivalent-circuit model figure.
Fig. 2 is overall system architecture theory diagram.
Detailed description of the invention
The present invention will be further described below in conjunction with the accompanying drawings.
Fig. 1 is electrokinetic cell RC equivalent-circuit model figure.
The state space equation of battery is obtained, in the equation, respectively according to the electrokinetic cell RC equivalent-circuit model set up
Parameter meaning is as follows:、WithRepresent the terminal voltage of battery, open-circuit voltage (OCV) and polarizing voltage respectively,Table
Show ohmage,WithRepresent inside battery concentration difference resistance and electrochemistry resistance respectively,Represent the memory capacity of battery.
Terminal voltage equation is can get as follows by Kirchhoff's second law:
。
Arrangement obtains battery status space equation:
。
Wherein,WithRepresent system external disturbance and modeling error.
And each parameter is expressed as follows in equation:
。
Before carrying out Design of Sliding Mode Observer, first determine whether the observability of system.
For the battery equivalent model set up, selected state variable is, input and output
It is respectively,, then battery status space equation can be reduced to.
。
Wherein
。
Then the observing matrix of system is
。
Obviously,Always full rank, so battery system is observable, can carry out Design of Sliding Mode Observer.
Carry out Design of Sliding Mode Observer below.
With the signum function improved as switching function, greatly reducing chattering phenomenon, described switching function designs
As follows:
。
Wherein。For positive number.
Design of Sliding Mode Observer is as follows:
。
Wherein,,WithIt is respectively,WithEstimated value,,WithFor sliding mode observer
Gain, and,。
State equation error is defined as follows:,,。
Thus obtaining battery error dynamical equation is
。
Will be proven below the stability of system, choosing Lyapunov function is:
。
This Lyapunov function derivation can be obtained:
。
Wherein,。
Thus can obtain:
。
By above-mentioned condition, obtain battery SOC error equation as follows:
。
In like manner, for proving the convergence of SOC error, choosing Lyapunov function is:
。
RightDerivation obtains
。
Wherein,。
Thus obtain:
。
Obtained by above-mentioned condition:
。
The above analysis can obtain,, meet stability condition, therefore designed system be stable.
Finally, obtain improve sliding mode observer equation:
。
Claims (8)
1. an electrokinetic cell SOC method of estimation, it is characterised in that comprising the concrete steps that of described electrokinetic cell SOC method of estimation:
Set up electrokinetic cell RC equivalent-circuit model, obtain the state-space model of electrokinetic cell；State according to electrokinetic cell model
Space equation, obtains the observing matrix of system, it is judged that the observability of system；With the signum function improved as switching letter
Number, designs sliding mode observer；Utilizing the sliding mode observer equation of battery status space equation and design, the error obtaining battery is moved
State equation；Choose Lyapunov function, stability condition obtain electrokinetic cell SOC and estimate equation.
2. a kind of electrokinetic cell SOC method of estimation as claimed in claim 1, it is characterised in that: described battery is lithium-ion electric
Pond.
3. electrokinetic cell RC equivalent-circuit model as claimed in claim 1, it is characterised in that: based on described RC equivalent circuit mould
Type and Kirchhoff's law, with the electric current of battery as input variable, the terminal voltage of battery is output variable, and according to open-circuit voltage
And the relation between SOC, using battery SOC as state variable, the state-space model obtaining electrokinetic cell is as follows:
It is reduced to
。
4. the system as claimed in claim 1 observing matrix, it is characterised in that: described systematic observation matrix is as follows:
Wherein
Obviously,Always full rank, so battery system is observable.
5. sliding mode observer switching function as claimed in claim 1, it is characterised in that: with the signum function improved as cutting
Exchange the letters number, greatly reduces chattering phenomenon, and the design of described switching function is as follows:
Wherein,For positive number.
6. sliding mode observer as claimed in claim 1, it is characterised in that: described Design of Sliding Mode Observer is as follows:
Wherein,,WithIt is respectively,WithEstimated value,,WithIncrease for sliding mode observer
Benefit.
7. battery error dynamical equation as claimed in claim 1, it is characterised in that: described error dynamics equation is as follows:
。
8. battery SOC as claimed in claim 1 estimates equation, it is characterised in that: described battery SOC estimates that equation is by glide
Mould observer equation obtains:
。
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510763417 | 2015-11-11 | ||
| CN2015107634178 | 2015-11-11 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105911480A true CN105911480A (en) | 2016-08-31 |
Family
ID=56751653
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610252852.9A Pending CN105911480A (en) | 2015-11-11 | 2016-04-22 | Power battery SOC estimation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105911480A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106597308A (en) * | 2016-12-16 | 2017-04-26 | 西南交通大学 | Power cell residual electricity quantity estimation method |
| CN108241128A (en) * | 2018-01-09 | 2018-07-03 | 西南交通大学 | A kind of proton exchange film fuel battery system method for estimating state |
| CN110082689A (en) * | 2019-05-21 | 2019-08-02 | 闽江学院 | A kind of energy internet energy-storage system lithium battery SOC method for estimating state |
| CN110221221A (en) * | 2019-04-24 | 2019-09-10 | 吉林大学 | Charge states of lithium ion battery and health status combined estimation method |
| CN110646739A (en) * | 2019-09-30 | 2020-01-03 | 闽江学院 | SOC state estimation method of multi-lithium battery parallel system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102645637A (en) * | 2012-04-25 | 2012-08-22 | 中航锂电（洛阳）有限公司 | Method for estimating SOC (state of charge) of equalized batteries |
| EP2667211A1 (en) * | 2011-01-18 | 2013-11-27 | Calsonic Kansei Corporation | Device for estimating state of charge of battery |
| EP2765436A1 (en) * | 2011-10-07 | 2014-08-13 | Calsonic Kansei Corporation | Battery state-of-charge estimation device and state-of-charge estimation method |
| CN104977545A (en) * | 2015-08-03 | 2015-10-14 | 电子科技大学 | Power battery charge state estimation method and system |
-
2016
- 2016-04-22 CN CN201610252852.9A patent/CN105911480A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2667211A1 (en) * | 2011-01-18 | 2013-11-27 | Calsonic Kansei Corporation | Device for estimating state of charge of battery |
| EP2765436A1 (en) * | 2011-10-07 | 2014-08-13 | Calsonic Kansei Corporation | Battery state-of-charge estimation device and state-of-charge estimation method |
| CN102645637A (en) * | 2012-04-25 | 2012-08-22 | 中航锂电（洛阳）有限公司 | Method for estimating SOC (state of charge) of equalized batteries |
| CN104977545A (en) * | 2015-08-03 | 2015-10-14 | 电子科技大学 | Power battery charge state estimation method and system |
Non-Patent Citations (2)
| Title |
|---|
| IL-SONG KIM: "Nonlinear State of Charge Estimator for Hybrid Electric Vehicle Battery", 《IEEE TRANSACTIONS ON POWER ELECTRONICS》 * |
| 何洪文 等: "基于滑模观测器的锂离子动力电池荷电状态估计", 《吉林大学学报（工学版）》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106597308A (en) * | 2016-12-16 | 2017-04-26 | 西南交通大学 | Power cell residual electricity quantity estimation method |
| CN106597308B (en) * | 2016-12-16 | 2018-12-25 | 西南交通大学 | A kind of power battery method for estimating remaining capacity |
| CN108241128A (en) * | 2018-01-09 | 2018-07-03 | 西南交通大学 | A kind of proton exchange film fuel battery system method for estimating state |
| CN110221221A (en) * | 2019-04-24 | 2019-09-10 | 吉林大学 | Charge states of lithium ion battery and health status combined estimation method |
| CN110082689A (en) * | 2019-05-21 | 2019-08-02 | 闽江学院 | A kind of energy internet energy-storage system lithium battery SOC method for estimating state |
| CN110646739A (en) * | 2019-09-30 | 2020-01-03 | 闽江学院 | SOC state estimation method of multi-lithium battery parallel system |
| CN110646739B (en) * | 2019-09-30 | 2022-03-04 | 闽江学院 | SOC state estimation method of multi-lithium battery parallel system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Moura et al. | PDE estimation techniques for advanced battery management systems—Part I: SOC estimation | |
| Dang et al. | Open-circuit voltage-based state of charge estimation of lithium-ion battery using dual neural network fusion battery model | |
| Corno et al. | Electrochemical model-based state of charge estimation for Li-ion cells | |
| Moura et al. | Adaptive partial differential equation observer for battery state-of-charge/state-of-health estimation via an electrochemical model | |
| CN105911480A (en) | Power battery SOC estimation method | |
| Zhang et al. | Modeling discharge behavior of multicell battery | |
| Lin et al. | Analytic bound on accuracy of battery state and parameter estimation | |
| Moura et al. | Adaptive PDE observer for battery SOC/SOH estimation | |
| Wang et al. | Online state of charge estimation for the aerial lithium-ion battery packs based on the improved extended Kalman filter method | |
| Guo et al. | SoC estimation of lithium battery based on AEKF algorithm | |
| Yu et al. | Fractional-order modeling of lithium-ion batteries using additive noise assisted modeling and correlative information criterion | |
| CN104991980A (en) | Electrochemical mechanism modeling method for lithium-ion battery | |
| Gao et al. | Research on PNGV model parameter identification of LiFePO4 Li-ion battery based on FMRLS | |
| CN105223512A (en) | Based on the method for the dynamic rectification dump energy of battery behavior | |
| Kim et al. | State of charge estimation based on a realtime battery model and iterative smooth variable structure filter | |
| JP2015215169A (en) | Parameter calculation device, parameter calculation method, and program | |
| Blondel et al. | Nonlinear circle-criterion observer design for an electrochemical battery model | |
| Lin | A data selection strategy for real-time estimation of battery parameters | |
| Kim et al. | Hysteresis modeling for model-based condition monitoring of lithium-ion batteries | |
| Zhang et al. | A data-driven based state of energy estimator of lithium-ion batteries used to supply electric vehicles | |
| CN104833856A (en) | Method and device for estimating internal resistance of battery | |
| Tian et al. | Parallel-connected battery module modeling based on physical characteristics in multiple domains and heterogeneous characteristic analysis | |
| Lin et al. | An enhanced circuit-based battery model with considerations of temperature effect | |
| CN110412471B (en) | Construction method of composite electrochemical polarization model of lithium ion battery pack | |
| Kim et al. | Online state of charge and electrical impedance estimation for multicell lithium-ion batteries |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20160831 |