COMPLEMENTARY ENGAGEMENT OF BATTERY BANKS TO AUGMENT LIFE, PERFORMANCE AND CAPACITY OF ENERGY STORAGE SYSTEM

1 . An energy storage system comprising:

a plurality of battery banks of individual batteries based on split configuration derived by a splitter, wherein split battery configuration of the plurality of banks varies based on a probability distribution function (pdf) of expected usage pattern, optimization goal, and battery characteristics of a corresponding single battery system; and

a logic unit, pre-configured with the pdf and connected to the plurality of battery banks, configured to:

obtain performance of each of the battery banks;

select at least one battery bank, from the plurality of battery banks, to provide power to a load based on current performance data of each said battery banks and at least one selection criterion; and

rotate use of battery banks from the plurality of battery banks until next charging opportunity;

wherein the split from a single battery bank is to optimize at least one among cost, weight or size of the system; and

wherein the selection of at least one battery bank is based on the pdf; and

wherein the selection of battery banks is to optimize at least one among weight, cost, size, and life of the system for the usage pattern without compromising on the range of the system.

2 . The system of claim 1 , wherein characteristic of each battery bank is different based on at least one among chemistry, variability in chemistry, energy density, size, weight, and cost.

3 . The system of claim 1 , wherein the required storage capacity is obtained by using plurality of battery banks aiding the performance, and reducing the total cost of the system by using the required battery bank or battery banks according to the selection criterion.

4 . The system of claim 1 , wherein said criteria is configured to select a battery bank out of the plurality of battery banks in a sequential order according to usage requirements based on pre-defined priorities for the plurality of battery banks or in an adaptive manner based on the matrices chosen for a given application.

5 . The system of claim 1 , wherein the logic unit is further configured to dynamically switch from a first energy harnessing mode to a second energy harnessing mode, wherein said harnessing modes are based on usage parameters.

6 . The system of claim 1 , wherein the selection criteria comprises at least one threshold dynamically defined based on the plurality of usage parameters.

7 . The system of claim 4 , wherein the selection criteria depends upon the said battery usage parameters comprising at least one among Depth of Discharge (DoD), rate of charging, rate of discharging, and operation temperature which vary based on the application usage of the system.

8 . The system of claim 5 , wherein the selection criteria depends upon the said battery usage parameters comprising at least one among Depth of Discharge (DoD), rate of charging, rate of discharging, and operation temperature which vary based on the application usage of the system.

9 . The system of claim 6 , wherein the selection criteria depends upon the said battery usage parameters comprising at least one among Depth of Discharge (DoD), rate of charging, rate of discharging, and operation temperature which vary based on the application usage of the system.

10 . The system of claim 1 , wherein performance data comprises at least one of a state of charge, generated current, generated voltage, state of health and lifetime of the battery bank(s).

11 . The system of claim 1 , said logic unit further configured to update its logic based on said pre-configured pdf with an updated pdf based on actual usage patterns observed.

12 . The system of claim 1 , wherein frequency of use of different battery banks and life of the batteries from said plurality of battery banks varies based on usage probability distribution function in use.

13 . An energy management method for an energy storage system configured with a plurality of battery banks, the method comprising:

deriving a split battery configuration with a plurality of battery banks by a splitter, wherein the split battery configuration of the plurality of banks varies based on a probability distribution function (pdf) of expected usage pattern, optimization goal, and battery characteristics of a corresponding single battery system;

obtaining, by the energy storage system, performance information of said plurality of battery banks;

selecting, by the energy storage system, at least one battery bank to provide power to a load based on desired performance and at least one selection criterion; and

rotating use of battery banks from the plurality of battery banks until next charging opportunity,

wherein the split from a single battery bank is to optimize at least one among cost, weight or size of the system, and

wherein the selection of at least one battery bank is based on the pdf, and

wherein the selection of battery banks is to optimize at least one among weight, cost, size, and life of the system for the usage pattern without compromising on the range of the system.

14 . The method of claim 13 , wherein characteristic of each battery bank is different based on at least one among chemistry, variability in chemistry, energy density, size, weight, and cost.

15 . The method of claim 13 , wherein the required storage capacity is obtained by using plurality of battery banks aiding the performance, and reducing the total cost of the system by using the required battery bank or battery banks according to the selection criterion.

16 . The method of claim 13 , wherein said criteria is configured to select a battery bank out of the plurality of battery banks in a sequential order according to usage requirements based on pre-defined priorities for the plurality of battery banks or in an adaptive manner based on the matrices chosen for a given application.

17 . The method of claim 13 , wherein the logic unit is further configured to dynamically switch from a first energy harnessing mode to a second energy harnessing mode, wherein said harnessing modes are based on usage parameters.

18 . The method of claim 13 , wherein the selection criteria comprises at least one threshold dynamically defined based on the plurality of usage parameters.

19 . The method of claim 14 , wherein the selection criteria depends upon the said battery usage parameters comprising at least one among Depth of Discharge (DoD), rate of charging, rate of discharging, and operation temperature which vary based on the application usage of the system.

20 . The method of claim 15 , wherein the selection criteria depends upon the said battery usage parameters comprising at least one among Depth of Discharge (DoD), rate of charging, rate of discharging, and operation temperature which vary based on the application usage of the system.

21 . The method of claim 16 , wherein the selection criteria depends upon the said battery usage parameters comprising at least one among Depth of Discharge (DoD), rate of charging, rate of discharging, and operation temperature which vary based on the application usage of the system.

22 . The method of claim 13 , wherein performance data comprises at least one of a state of charge, generated current, generated voltage, state of health and lifetime of the battery bank(s).

23 . The method of claim 13 , said logic unit further configured to update its logic based on said pre-configured pdf with an updated pdf based on actual usage patterns observed.

24 . The method of claim 13 , wherein frequency of use of different battery banks and life of the batteries from said plurality of battery banks varies based on usage probability distribution function in use.