Method and device for optimized recharging of an electric battery

• US 9,487,097 B2
• Filed: 09/06/2012
• Issued: 11/08/2016
• Est. Priority Date: 09/07/2011
• Status: Expired due to Fees

• Current Assignee: Electricitã© De France, Electricite Reseau Distribution France (Electricitã© De France)
• Original Assignee: Electricitã© De France, Electricite Reseau Distribution France (Electricitã© De France)
• Inventors: Rousselle, Mlaine, Alberdi, Gaizka
• Primary Examiner(s): Kik, Phallaka
• Application Number:
  US14/343,209
• Publication Number:
  US 20140217993A1
• Time in Patent Office: 1,524 Days
• Field of Search: 320/157, 320/132, 320/104, 307/429, 340/636.12, 340/636.16
• US Class Current: 1/1
• CPC Class Codes: B60L 2200/12 Bikes
• CPC Class Codes: B60L 2240/70 Interactions with external data bases, e.g. traffic centres
• CPC Class Codes: B60L 2240/80 Time limits
• CPC Class Codes: B60L 53/00 Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
• CPC Class Codes: B60L 53/31 Charging columns specially adapted for electric vehicles
• CPC Class Codes: B60L 53/63 in response to network capacity
• CPC Class Codes: B60L 53/68 Off-site monitoring or control, e.g. remote control
• CPC Class Codes: G01N 27/416 Systems G01N27/27 takes precedence
• CPC Class Codes: G08B 21/00 Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
• CPC Class Codes: H02J 2310/48 for electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: H02J 7/00712 the cycle being controlled or terminated in response to electric parameters
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 Electric charging stations
• CPC Class Codes: Y02T 90/14 Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 : Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 10/126 : the energy generation units being or involving electric vehicles [EV] or hybrid vehicles [HEV], i.e. power aggregation of EV or HEV, vehicle to grid arrangements [V2G]
• CPC Class Codes: Y04S 20/222 : Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/242 : Home appliances
• CPC Class Codes: Y04S 30/12 : Remote or cooperative charging

Abstract

A method of optimized recharging of the electric battery of at least one electrical system by an electrical recharging device, in which the electric battery is recharged during at least one time interval by applying a charging power level associated with this time interval, this time interval belonging to an available charging time period initiated by the connecting of the recharging system of the electric battery to the electrical recharging device, and the charging power level being determined as a function of a charging curve associated with the electrical recharging device and of the residual electrical energy contained in the electric battery upon the connecting of the electric battery charging system to the electrical recharging device.

Claims

1. A method for the optimized recharging of an electric battery of at least one electrical system by an electrical recharging device, said at least one electrical system being an electric vehicle,

the method comprising:

determining an available charging time period between a moment when the electrical recharging device is connected to the electric battery and a moment when the electrical recharging device is disconnected from the electric battery;

recharging the electric battery during at least one recharge interval within the available charging time period, said at least one recharge interval comprising k charging time intervals during each of which a respective charging power level is applied to recharge the electric battery;

wherein said respective charging power is determined by;

determining a residual electrical energy in the electric battery;

for each of the k charging time intervals;

sampling a load curve associated with the electrical recharging device over the available charging time period in order to obtain a set of load curve power values respectively associated with consecutive time intervals within the available charging time period;

sorting, in ascending order, the load curve power values in order to obtain a set of sorted load curve power values;

determining the respective charging power level of each of the k charging time intervals as a function of the residual electrical energy and of a k+1^th load curve power value of the set of sorted load curve power values, the k charging time intervals being respectively associated with k first values of the set of sorted load curve power values.

2. The optimized recharging method according to claim 1, wherein determining the charging power levels applied during said k charging time intervals comprises the following steps, executed while an index k, starting from an initial value of 1, is incremented:

associating, for the k time intervals associated with the k first values of the sorted load curve power values, a load curve power value at rank k that is equal to the k+1^th load curve power value of the set of sorted load curve power values;

calculating, for each of the k time intervals associated with the k first values of the set of sorted load curve power values, a charging power level at rank k associated with said time interval, said charging power level at rank k being determined as a function of a difference between the load curve power value at rank k and the load curve power value which are associated with said time interval;

comparing an electrical energy at rank k, determined by applying the charging power levels at rank k to the k time intervals with which they are respectively associated, with an electrical energy required to recharge the battery;

incrementing the index k if the electrical energy at rank k is less than or equal to the energy required to recharge the battery.

3. The optimized recharging method according to claim 2, wherein, for each of the k time intervals associated with the k first values of the sorted load curve power values, the charging power level at rank k associated with said time interval is equal to a minimum value between, on the one hand, a maximum load curve power value, and on the other hand, a difference between the load curve power value at rank k and the load curve power value which are associated with said time interval.

4. The optimized recharging method according to claim 2, wherein, when the electrical energy at rank k is greater than the energy required to recharge the battery, for each of the k time intervals associated with the k first values of the sorted load curve power values, the charging power level at rank k associated with said time interval is equal to a minimum value between, on the one hand, a maximum load curve power value, and on the other hand, a sum of the charging power level at rank k−

1 and of a difference between the energy required and the electrical energy at rank k−

1 divided by the number k.

5. The optimized recharging method according to claim 2, wherein, when the electrical energy at rank k is less than or equal to the energy required to recharge the battery, said determining the charging power levels further comprises comparing a charging duration at rank k, equal to a sum of the k time intervals associated with the k first values of the sorted load curve power values, and a duration of the available charging time period, the index k only being incremented if the charging duration at rank k is less than or equal to the duration of the available charging time period.

6. The optimized recharging method according to claim 5, wherein, when the charging duration at rank k is greater than the duration of the available charging time period and when the electrical energy at rank k differs from the energy required to recharge the battery by at least a predetermined difference, said determining the charging power levels includes calculating, for each consecutive time interval of the available time period, a charging power level to be applied which is equal to a minimum value between, on the one hand, a maximum load curve power value, and on the other hand, a sum of the power level at rank k associated with said time interval and a difference between the electrical energy at rank k and the required energy divided by the number k.

7. The optimized recharging method according to claim 1, wherein the recharging of the electric battery further comprises, for each of the charging time intervals with which a charging power level is associated, comparing a limit capacity level associated with said charging time interval and an estimated increased load curve power value equal to a sum of the load curve power value and of the charging power level which are associated with said charging time interval, the charging power level only being applied, during said charging time interval, if said estimated increased load curve power value is less than a limit capacity level associated with said charging time interval.

8. The optimized recharging method according to claim 7, wherein, for each charging time interval for which the estimated increased load curve power value is greater than or equal to the limit capacity level associated with said charging time interval, said each charging time interval is associated with a charging power value substantially equal to a difference between the limit capacity level and the load curve power value which are associated with said charging time interval.

9. The optimized recharging method according to claim 1, wherein the available charging time period is determined as a function of the moment when the electric battery recharging system is connected to the electrical recharging device and of an indication concerning a charging end time provided by a user of the electric vehicle.

10. The optimized recharging method according to claim 1, further comprising, prior to recharging the electric battery, verifying that the available charging time period has a duration sufficient for fully recharging the electric battery, and said recharging of the electric battery during said at least one charging time interval occurs only if the duration of the available charging time period is greater than a length of time required for fully recharging the electric battery.

11. The optimized recharging method according to claim 1, wherein the electric battery is to be modulated in charging power and has substantially no memory effect.

12. A non-transitory computer readable storage medium, having stored thereon a computer program comprising program instructions, the computer program being loadable into a data-processing unit and adapted to cause the data-processing unit to carry out the steps of claim 1 when the computer program is run by the data-processing unit.

13. An optimized recharging device for recharging at least one electric vehicle, connected to an electrical grid and comprising at least one connection port suitable for connection to the electric battery of an electric vehicle, the device being configured to implement the steps of the method according to claim 1 after the electric battery of an electric vehicle is connected to the connection port of the optimized recharging device.

14. An optimized recharging system for electrically recharging a fleet composed of at least one electric vehicle, the system comprising an electrical grid and the electrical recharging device according to claim 13, connected to said electrical grid.

15. The optimized recharging system according to claim 14, further comprising a remote computer system, connected to the optimized recharging device and comprising a processing unit suitable for carrying out the steps of the method according to claim 1.