JP2006138858A - 車両用鉛蓄電池の内部状態検出システム - Google Patents
車両用鉛蓄電池の内部状態検出システム Download PDFInfo
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- JP2006138858A JP2006138858A JP2005336134A JP2005336134A JP2006138858A JP 2006138858 A JP2006138858 A JP 2006138858A JP 2005336134 A JP2005336134 A JP 2005336134A JP 2005336134 A JP2005336134 A JP 2005336134A JP 2006138858 A JP2006138858 A JP 2006138858A
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- 239000002253 acid Substances 0.000 title claims abstract description 33
- 238000001514 detection method Methods 0.000 title claims description 14
- 238000013528 artificial neural network Methods 0.000 claims abstract description 30
- 238000007599 discharging Methods 0.000 claims abstract description 4
- 239000013598 vector Substances 0.000 claims description 15
- 230000002596 correlated effect Effects 0.000 claims 1
- 230000008878 coupling Effects 0.000 description 17
- 238000010168 coupling process Methods 0.000 description 17
- 238000005859 coupling reaction Methods 0.000 description 17
- 238000000034 method Methods 0.000 description 17
- 230000006870 function Effects 0.000 description 13
- 238000010586 diagram Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 7
- 230000004048 modification Effects 0.000 description 5
- 238000012986 modification Methods 0.000 description 5
- 230000008901 benefit Effects 0.000 description 3
- 230000010354 integration Effects 0.000 description 3
- 230000006866 deterioration Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000000593 degrading effect Effects 0.000 description 1
- 239000003792 electrolyte Substances 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 229910052744 lithium Inorganic materials 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
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- 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]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
-
- 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]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
-
- 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]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
-
- 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]
- G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
-
- 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]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
Abstract
【解決手段】車載電気装置に電力供給する鉛蓄電池と、鉛蓄電池の充電及び放電の電流値を検出する手段と、鉛蓄電池の端子電圧値を検出する手段とを備え、鉛蓄電池の電流値と端子電圧とを入力とするニューラルネットワークによって、鉛蓄電池の内部状態量を学習して出力するシステムであって、ニューラルネットワークには、鉛蓄電池の型式情報が入力される。電流値及び前記端子電圧値を過去の履歴情報を重畳することで、ヒステリシスを含む相関を得る。
【選択図】図1
Description
34B19:27:27
46B24:36:36
55D23:48:48
80D26:55:55
105D31:64:64
連続量としてあらわすメリットは、例えばニューラルネットワーク部52の学習を予め上記の34B19:27:27、55D23:48:48及び105D31:64:64の3種類で実行しておけば、未学習型式46B24:36:36及び80D26:55:55は、学習結果から内挿補間で対応できることである。
また、中間層のk番目のセル522からの出力信号OUTk(t)は、以下の式(2)のようになる。
ここで、式(2)のf(x)は、シグモイド関数と呼ばれる非線形関数であり、以下の式(3)のように定義される関数である。
また、中間層のk番目のセル522と出力層のセル523との結合係数をWkとすると、出力層への入力信号INPUTo(t)は、以下の式(4)のようになる。
そして、時刻tにおける出力信号OUTsoc(t)(残存容量を表す信号)は、以下の式(5)のようになる。
なお、学習過程とは、時刻tにおける最終の出力信号OUTsoc(t)が教師信号(真値)との誤差を最小にするように、各セル間の結合係数を最適化することである。
ここで、式(6)の△Wkは、以下の式(7)のように定義される。
=η*{OUTsoc(t)−tar(t)}*{∂OUTsoc(t)/∂Wk}
=η*{OUTsoc(t)−tar(t)}*L*{∂INPUTo(t)/∂Wk}
=η*L*{OUTsoc(t)−tar(t)}*OUTk(t)・・・・・(7)
また、式(7)のEkは、教師データとネットワーク出力の誤差を表す量で以下の式(8)のように定義される。
次に、中間層のk番目のセル522と入力層のj番目のセル521との結合係数Wjkの更新ルールについて説明する。
ここで、式(9)の△Wjkは、以下の式(10)のように定義される。
=−η*{∂Ek/∂INPUTk(t)}*{∂INPUTk(t)/∂Wj k}
=−η*{∂Ek/∂OUTk(t)}*{∂OUTk(t)/∂INPUTk(t)}*Ij
=−η*{∂Ek/∂OUTsoc(t)}*{∂OUTsoc(t)/∂INPUTo}*{∂INPUTo/OUTk(t)}*f’(INPUTk(t)+b)*Ij
=−η*(OUTsoc(t)−tar(t))*L*Wk*f’(INPUTk(t)+b)*Ij
=−η*L*Wk*Ij*(OUTsoc(t)−tar(t))*f’(INPUTk(t)+b)・・・・・(10)
このように更新された新たな結合係数Wk、Wjkによって、再び出力信号OUTsoc(t)を計算し、誤差関数Ekが所定の微小値以下になるまで結合係数Wk、Wjkを更新しつづける。
第2の実施例では、ニューラルネットワーク部52への入力値として蓄電池の充放電の電流値及び端子電圧値の履歴をもつデータ列をベクトルと表現する。なお、電流値の履歴データ列を電流履歴ベクトルと、端子電圧値の履歴データ列を電圧履歴ベクトルと呼ぶ。
本実施例の変形例を以下に示す。
2…発電機、
3…電気装置、
4…電流センサ、
5…状態検知装置、
51…メモリ、
52…ニューラルネットワーク部、
53…バッファ部、
6…発電機制御装置。
Claims (4)
- 車載電気装置に電力供給する鉛蓄電池と、前記鉛蓄電池の充電及び放電の電流値を検出する手段と、前記鉛蓄電池の端子電圧値を検出する手段とを備え、前記鉛蓄電池の前記電流値と前記端子電圧とを入力とするニューラルネットワークによって、前記鉛蓄電池の内部状態量を学習して出力する車両用鉛蓄電池の内部状態検出システムにおいて、
前記ニューラルネットワークには、前記鉛蓄電池の型式情報を入力すると共に、
前記電流値及び前記端子電圧値を過去の履歴情報を重畳することで、ヒステリシスを含む相関を得ることを特徴とする車両用鉛蓄電池の内部状態検出システム。 - 前記前記鉛蓄電池の型式情報は、定格容量であることを特徴とする請求項1記載の車両用鉛蓄電池の内部状態検出システム。
- 前記電流値及び前記端子電圧値を履歴ベクトルとして入力することを特徴とする請求項1もしくは2記載の車両用鉛蓄電池の内部状態検出システム。
- 前記型式情報は、連続量であらわされ、且つ前記鉛蓄電池の内部インピーダンスに相関ある数値であることを特徴とする請求項1ないし3のいずれかに記載の車両用鉛蓄電池の内部状態検出システム。
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JP2005336134A JP4075925B2 (ja) | 2003-04-15 | 2005-11-21 | 車両用鉛蓄電池の内部状態検出システム |
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JP2003110652A JP3935099B2 (ja) | 2003-04-15 | 2003-04-15 | 車両用蓄電装置の内部状態検出システム |
JP2003110651 | 2003-04-15 | ||
JP2003420483A JP4379106B2 (ja) | 2003-04-15 | 2003-12-18 | 車両用蓄電装置の内部状態検出システム |
JP2005336134A JP4075925B2 (ja) | 2003-04-15 | 2005-11-21 | 車両用鉛蓄電池の内部状態検出システム |
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JP4075925B2 JP4075925B2 (ja) | 2008-04-16 |
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JP2003110652A Expired - Lifetime JP3935099B2 (ja) | 2003-04-15 | 2003-04-15 | 車両用蓄電装置の内部状態検出システム |
JP2003420483A Expired - Fee Related JP4379106B2 (ja) | 2003-04-15 | 2003-12-18 | 車両用蓄電装置の内部状態検出システム |
JP2005336134A Expired - Fee Related JP4075925B2 (ja) | 2003-04-15 | 2005-11-21 | 車両用鉛蓄電池の内部状態検出システム |
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JP2003110652A Expired - Lifetime JP3935099B2 (ja) | 2003-04-15 | 2003-04-15 | 車両用蓄電装置の内部状態検出システム |
JP2003420483A Expired - Fee Related JP4379106B2 (ja) | 2003-04-15 | 2003-12-18 | 車両用蓄電装置の内部状態検出システム |
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US (1) | US20040207367A1 (ja) |
EP (1) | EP1469321A1 (ja) |
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2004
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WO2019021095A1 (ja) * | 2017-07-26 | 2019-01-31 | 株式会社半導体エネルギー研究所 | 二次電池の充電制御システム及び二次電池の異常検出方法 |
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EP1469321A1 (en) | 2004-10-20 |
JP2004317256A (ja) | 2004-11-11 |
JP2004333472A (ja) | 2004-11-25 |
JP4075925B2 (ja) | 2008-04-16 |
US20040207367A1 (en) | 2004-10-21 |
JP3935099B2 (ja) | 2007-06-20 |
JP4379106B2 (ja) | 2009-12-09 |
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