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Patent · US2011025258A1 · A1 · US

System for scheduling battery charge and discharge

(11) Publication number
US2011025258A1
(21) Application number
US-84604910-A
(22) Filing date
2010-07-29
(30) Priority date
2009-07-29
(43) Publication date
2011-02-03
(52) CPC
  • H01M Processes or means, e.g. batteries, for the direct conversion of chemical energy into electrical energy: 10/425, 10/441, 2010/4271, 2220/20
  • H02J Electric power networks; circuit arrangements or systems for supplying or distributing electric power; systems for storing electric energy: 7/50, 7/575, 7/585, 7/855, 7/92
  • Y02E Reduction of greenhouse gas [ghg] emissions, related to energy generation, transmission or distribution: 60/10
(73) Assignee
UNIV MICHIGAN
(54) Title
System for scheduling battery charge and discharge
(57) Abstract

Effective scheduling of battery charge and discharge activities, by making the most of battery characteristics, can extend the battery pack's operation-time and lifetime. A system and method for scheduling battery activities is disclosed. This framework dynamically adapts battery activities to load demands and to the condition of individual battery cells, thereby extending the battery pack's operation-time and making them robust to anomalous voltage imbalances. The scheduling framework includes two components. An adaptive filter estimates the upcoming load demand. Based on the estimated load demand, a scheduler can determine the number of parallel-connected battery cells to be discharged. The scheduler also effectively partitions the battery cells in a pack, allowing the battery cells to be simultaneously charged and discharged in coordination with a reconfigurable battery circuit.

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Claims (1)

  1. A battery management system, comprising: a plurality of battery cells arranged in reconfigurable circuit paths; a plurality of switches selectively interconnecting battery cells to one of charge terminals and discharge terminals; and a scheduling module that: receives an estimated load demand for the plurality of battery cells; determines a subset of the plurality of battery cells needed to meet the load demand, wherein the number of battery cells in the determined subset is inversely correlated to a rate at which the plurality of battery cells recover voltage in a rest state; and controls the plurality of switches to connect the subset of battery cells to the discharge terminals and to connect a remainder of the plurality of battery cells to the charge terminals. 2. The battery management system of claim 1 wherein the scheduling module partitions the plurality of battery cells into a group of cells eligible for discharging and another group of cells eligible for charging, wherein the scheduling module selects the subset of the plurality of battery cells needed to meet the load demand from the group of cells eligible for discharging. 3. The battery management system of claim 2 wherein the scheduling module selects battery cells having the highest state of charge in the group of cells eligible for discharging to be in the subset of the plurality of battery cells. 4. The battery management system of claim 3 wherein the scheduling module partitions the plurality of cells based on state of charge of a given battery cell in relation to a threshold, where the threshold is adjusted dynamically by the scheduling module based on the estimated load demand, an estimated maximum load demand, and a nominal capacity for the plurality of cells. 5. The battery management system of claim 1 wherein scheduling module calculates the number of battery cells in the subset by: k = d * v, wherein d* is the estimated load demand and v is the rate at which the plurality of battery cells recover voltage in a rest state. 6. The battery management system of claim 1 further comprising an adaptive filter that receives previous load demands and estimates the load demand based on the previous load demands, wherein the previous load demands indicate an amount of power required by a plurality of applications at a specific time. 7. The battery management system of claim 1 wherein the adaptive filter performs a regression on the previous load demands to estimate the load demand. 8. The battery management system of claim 1 wherein the scheduling module coordinates charging of the battery cells in the group of cells eligible for charging while the battery cells in the group of cells eligible for discharging are being discharged. 9. The battery management system of claim 8 wherein the scheduling module selects a battery cell having the lowest state of charge in the group of cells eligible for charging, charges the selected battery cell until its state of charge reaches an average state of charge of the battery cells in the group of cells eligible for discharging, and reassigns the selected battery cell the group of cells eligible for discharging. 10. A method for scheduling battery cells for charging and discharging in a reconfigurable battery system, comprising: monitoring state of charge for each of a plurality of battery cells; partitioning the plurality of battery cells into a group of cells eligible for discharging and another group of cells eligible for charging in accordance with the state of charge of the battery cells; charging one or more battery cells in the group of cells eligible for charging while one or more battery cells in the group of cells eligible for discharging are being discharged; and reassigning the plurality of battery cells into either the group of cells eligible for discharging or the group of cells eligible for charging after the step of charging one or more battery cells. 11. The method of claim 10 further comprises selecting a subset of battery cells from the group of cells eligible for discharging and discharging the battery cells in the subset, where a number of battery cells in the subset of battery cells is inversely correlated to a rate at which the plurality of battery cells recover voltage in a rest state. 12. The method of claim 11 further comprises determining an estimated load demand from the plurality of battery cells using a recursive least squares method. 13. The method of claim 12 further comprises calculating the number of battery cells, k, in the subset by: k = d * v, wherein d* is the estimated load demand and v is the rate at which the plurality of battery cells recover voltage in a rest state. 14. The method of claim 11 further comprises selecting battery cells having the highest state of charge in the group of cell eligible for discharging to be the subset. 15. The method of claim 11 further comprises selecting a scheduling method based on the number of battery cells in the subset. 16. The method of claim 10 wherein charging one or more battery cells further comprises selecting a battery cell having the lowest state of charge in the group of cells eligible for charging, charging the selected battery cell until its state of charge reaches an average state of charge of the battery cells in the group of cells eligible for discharging, and reassigning the selected battery cell the group of cells eligible for discharging. 17. The method of claim 10 further comprises discharging battery cells in the group of cells eligible for discharging for a period of time while bypassing a given battery cell in the group of cells eligible for discharging having the lowest state of charge in the group of cells eligible for discharging. 18. The method of claim 17 further comprises determining state of charge for each of the battery cells in the group of cells eligible for discharging, determining a median state of charge for the battery cells in the group of cells eligible for discharging, and computing the period of time as a function of the median. 19. The method of claim 17 further comprises determining state of charge for each of the battery cells in the group of cells eligible for discharging, determining a median state of charge for the battery cells in the group of cells eligible for discharging, and discharging the battery cells in the group of cells eligible for discharging by an amount equal to the median.

Citations (13)

  • US2004101744A1
  • US2005052154A1
  • US2005242776A1
  • US2006092583A1
  • US2006164038A1
  • US2009085553A1
  • US4175249A
  • US4894764A
  • US5898291A
  • US6873133B1
  • US7075194B2
  • US7609031B2
  • US7692404B2
Record as JSON
{
  "publication_number": "US2011025258A1",
  "country": "US",
  "kind": "A1",
  "title": "System for scheduling battery charge and discharge",
  "abstract": "Effective scheduling of battery charge and discharge activities, by making the most of battery characteristics, can extend the battery pack's operation-time and lifetime. A system and method for scheduling battery activities is disclosed. This framework dynamically adapts battery activities to load demands and to the condition of individual battery cells, thereby extending the battery pack's operation-time and making them robust to anomalous voltage imbalances. The scheduling framework includes two components. An adaptive filter estimates the upcoming load demand. Based on the estimated load demand, a scheduler can determine the number of parallel-connected battery cells to be discharged. The scheduler also effectively partitions the battery cells in a pack, allowing the battery cells to be simultaneously charged and discharged in coordination with a reconfigurable battery circuit.",
  "claims": [
    "1. A battery management system, comprising: a plurality of battery cells arranged in reconfigurable circuit paths; a plurality of switches selectively interconnecting battery cells to one of charge terminals and discharge terminals; and a scheduling module that: receives an estimated load demand for the plurality of battery cells; determines a subset of the plurality of battery cells needed to meet the load demand, wherein the number of battery cells in the determined subset is inversely correlated to a rate at which the plurality of battery cells recover voltage in a rest state; and controls the plurality of switches to connect the subset of battery cells to the discharge terminals and to connect a remainder of the plurality of battery cells to the charge terminals. 2. The battery management system of claim 1 wherein the scheduling module partitions the plurality of battery cells into a group of cells eligible for discharging and another group of cells eligible for charging, wherein the scheduling module selects the subset of the plurality of battery cells needed to meet the load demand from the group of cells eligible for discharging. 3. The battery management system of claim 2 wherein the scheduling module selects battery cells having the highest state of charge in the group of cells eligible for discharging to be in the subset of the plurality of battery cells. 4. The battery management system of claim 3 wherein the scheduling module partitions the plurality of cells based on state of charge of a given battery cell in relation to a threshold, where the threshold is adjusted dynamically by the scheduling module based on the estimated load demand, an estimated maximum load demand, and a nominal capacity for the plurality of cells. 5. The battery management system of claim 1 wherein scheduling module calculates the number of battery cells in the subset by: k = d * v, wherein d* is the estimated load demand and v is the rate at which the plurality of battery cells recover voltage in a rest state. 6. The battery management system of claim 1 further comprising an adaptive filter that receives previous load demands and estimates the load demand based on the previous load demands, wherein the previous load demands indicate an amount of power required by a plurality of applications at a specific time. 7. The battery management system of claim 1 wherein the adaptive filter performs a regression on the previous load demands to estimate the load demand. 8. The battery management system of claim 1 wherein the scheduling module coordinates charging of the battery cells in the group of cells eligible for charging while the battery cells in the group of cells eligible for discharging are being discharged. 9. The battery management system of claim 8 wherein the scheduling module selects a battery cell having the lowest state of charge in the group of cells eligible for charging, charges the selected battery cell until its state of charge reaches an average state of charge of the battery cells in the group of cells eligible for discharging, and reassigns the selected battery cell the group of cells eligible for discharging. 10. A method for scheduling battery cells for charging and discharging in a reconfigurable battery system, comprising: monitoring state of charge for each of a plurality of battery cells; partitioning the plurality of battery cells into a group of cells eligible for discharging and another group of cells eligible for charging in accordance with the state of charge of the battery cells; charging one or more battery cells in the group of cells eligible for charging while one or more battery cells in the group of cells eligible for discharging are being discharged; and reassigning the plurality of battery cells into either the group of cells eligible for discharging or the group of cells eligible for charging after the step of charging one or more battery cells. 11. The method of claim 10 further comprises selecting a subset of battery cells from the group of cells eligible for discharging and discharging the battery cells in the subset, where a number of battery cells in the subset of battery cells is inversely correlated to a rate at which the plurality of battery cells recover voltage in a rest state. 12. The method of claim 11 further comprises determining an estimated load demand from the plurality of battery cells using a recursive least squares method. 13. The method of claim 12 further comprises calculating the number of battery cells, k, in the subset by: k = d * v, wherein d* is the estimated load demand and v is the rate at which the plurality of battery cells recover voltage in a rest state. 14. The method of claim 11 further comprises selecting battery cells having the highest state of charge in the group of cell eligible for discharging to be the subset. 15. The method of claim 11 further comprises selecting a scheduling method based on the number of battery cells in the subset. 16. The method of claim 10 wherein charging one or more battery cells further comprises selecting a battery cell having the lowest state of charge in the group of cells eligible for charging, charging the selected battery cell until its state of charge reaches an average state of charge of the battery cells in the group of cells eligible for discharging, and reassigning the selected battery cell the group of cells eligible for discharging. 17. The method of claim 10 further comprises discharging battery cells in the group of cells eligible for discharging for a period of time while bypassing a given battery cell in the group of cells eligible for discharging having the lowest state of charge in the group of cells eligible for discharging. 18. The method of claim 17 further comprises determining state of charge for each of the battery cells in the group of cells eligible for discharging, determining a median state of charge for the battery cells in the group of cells eligible for discharging, and computing the period of time as a function of the median. 19. The method of claim 17 further comprises determining state of charge for each of the battery cells in the group of cells eligible for discharging, determining a median state of charge for the battery cells in the group of cells eligible for discharging, and discharging the battery cells in the group of cells eligible for discharging by an amount equal to the median."
  ],
  "cpc": [
    "H01M 10/425",
    "H01M 10/441",
    "H01M 2010/4271",
    "H01M 2220/20",
    "H02J 7/50",
    "H02J 7/575",
    "H02J 7/585",
    "H02J 7/855",
    "H02J 7/92",
    "Y02E 60/10"
  ],
  "assignees": [
    "UNIV MICHIGAN"
  ],
  "filing_date": "2010-07-29",
  "publication_date": "2011-02-03",
  "priority_date": "2009-07-29",
  "application_number": "US-84604910-A",
  "family_id": "43526344",
  "citations": [
    "US2004101744A1",
    "US2005052154A1",
    "US2005242776A1",
    "US2006092583A1",
    "US2006164038A1",
    "US2009085553A1",
    "US4175249A",
    "US4894764A",
    "US5898291A",
    "US6873133B1",
    "US7075194B2",
    "US7609031B2",
    "US7692404B2"
  ]
}

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