Patent Application
20240332655
The present invention relates to battery systems and configurations, and more specifically, to systems and methods for configuring battery packs used in computer systems to obtain optimal battery performance and functional operational period for the battery packs.
Reliability of battery packs can significantly influence uninterrupted operation of computer systems. For example, an internal battery feature (IBF) with battery packs as a local uninterrupted power source can enhance the robustness of the power design of a mainframe system and decrease power line disturbance to the mainframe. Higher performing battery packs are needed for computer systems.
Embodiments of the present disclosure provide systems and methods for configuring battery packs, such as used in computer systems. The disclosed systems and methods provide an optimal battery configuration of battery cell types in the battery pack, improving battery performance and a functional operational period for the battery pack, assigning an optimal battery type to each battery cell in a linear battery cell string of the battery pack.
A disclosed non-limiting computer-implemented method comprises receiving predefined characteristics of multiple different candidate battery cell types and a desired number and voltage of a plurality of battery cells to be used to form a linear battery cell string for a battery pack. The system determines, for each position of the battery cells in the linear cell string, battery parameters for each of the different candidate cell types. The parameters comprise at least one of computed battery temperature, computed battery usable capacity, or computed battery efficiency. The system formulates an integer linear problem to optimize a battery configuration for the battery pack based on the battery parameters. The system solves the integer linear problem to select, one of the different candidate battery types to place at each of the positions of the battery cells in the linear cell string.
Other disclosed embodiments include a computer system and computer program product for configuring battery packs, implementing features of the above-disclosed method.
Embodiments of the disclosure provide systems and methods for configuring battery packs, for example used in computer systems. In one embodiment, the battery pack comprises a number (N) of cells connected together in a linear cell string, and a number (M) of battery cell types. A goal for implementing enhanced battery pack performance comprises identifying an optimized battery configuration, assigning a battery cell type for each position of battery cells in the linear battery cell string in the battery pack. A plurality of inputs are accessed, such as array of M different types of battery cells and an array of N batteries. Additional inputs accessed include, for example, a graph of temperature versus usable battery capacity, a graph of discharge current versus thermal dissipation, a cost of the battery (B_cost), other factors affecting battery performance efficiency, a temperature gradient versus location in a given battery pack and a position of a given battery in the battery pack. For each battery cell, selected parameters such as related to battery pack efficiency are determined, such as computed battery temperature, computed battery usable capacity, and computed battery efficiency. In one example, the system formulates and solves an integer linear problem and assigns a battery type to each position of the battery cells in the linear battery cell string of the battery pack.
In disclosed embodiments, a metal structure having high thermal conductivity, such as a metal mesh structure is positioned in contact engagement with battery cells at identified positions. The metal mesh structures can provide cooling to compensate for a difference in surface temperature of battery cells at different positions of a battery cell string of the battery pack, to provide optimal battery cell capacity with a more uniform surface temperature of all the battery cells. The surface temperature of battery cells can vary by position of battery cells of the battery pack, with battery cells at some positions having a lower surface temperature than other battery cells. In disclosed embodiments, the metal mesh structure is positioned with selected pairs of battery cells (e.g., to maintain in the desired surface temperature range of the selected battery cells), to achieve optimal battery capacity. The cooling metal mesh structures are configured to reduce flow impedance to a cooling flow path of the battery pack, while reducing battery cell surface temperature gradients by position of battery cells of the linear battery cell string of the battery pack. However, the metal mesh structures can be used independently of the battery positioning techniques discussed herein. For example, the metal mesh structure can be used to cool a single battery (e.g., battery cell), or to cool batteries arranged in a 2D or 3D array.
In one embodiment, the cooling porous metal mesh structure is formed of an Aluminum or Copper cylindrical mesh structure. For example, the cylindrical metal mesh structure is readily deformable, enabling battery pack installation and removal for example for battery cell servicing.
The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
In the following, reference is made to embodiments presented in this disclosure. However, the scope of the present disclosure is not limited to specific described embodiments. Instead, any combination of the following features and elements, whether related to different embodiments or not, is contemplated to implement and practice contemplated embodiments. Furthermore, although embodiments disclosed herein may achieve advantages over other possible solutions or over the prior art, whether or not a particular advantage is achieved by a given embodiment is not limiting of the scope of the present disclosure. Thus, the following aspects, features, embodiments and advantages are merely illustrative and are not considered elements or limitations of the appended claims except where explicitly recited in a claim(s). Likewise, reference to “the invention” shall not be construed as a generalization of any inventive subject matter disclosed herein and shall not be considered to be an element or limitation of the appended claims except where explicitly recited in a claim(s).
Various aspects of the present disclosure are described by narrative text, flowcharts, block diagrams of computer systems and/or block diagrams of the machine logic included in computer program product (CPP) embodiments. With respect to any flowcharts, depending upon the technology involved, the operations can be performed in a different order than what is shown in a given flowchart. For example, again depending upon the technology involved, two operations shown in successive flowchart blocks may be performed in reverse order, as a single integrated step, concurrently, or in a manner at least partially overlapping in time.
A computer program product embodiment (“CPP embodiment” or “CPP”) is a term used in the present disclosure to describe any set of one, or more, storage media (also called “mediums”) collectively included in a set of one, or more, storage devices that collectively include machine readable code corresponding to instructions and/or data for performing computer operations specified in a given CPP claim. A “storage device” is any tangible device that can retain and store instructions for use by a computer processor. Without limitation, the computer readable storage medium may be an electronic storage medium, a magnetic storage medium, an optical storage medium, an electromagnetic storage medium, a semiconductor storage medium, a mechanical storage medium, or any suitable combination of the foregoing. Some known types of storage devices that include these mediums include: diskette, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), static random access memory (SRAM), compact disc read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanically encoded device (such as punch cards or pits/lands formed in a major surface of a disc) or any suitable combination of the foregoing. A computer readable storage medium, as that term is used in the present disclosure, is not to be construed as storage in the form of transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide, light pulses passing through a fiber optic cable, electrical signals communicated through a wire, and/or other transmission media. As will be understood by those of skill in the art, data is typically moved at some occasional points in time during normal operations of a storage device, such as during access, de-fragmentation or garbage collection, but this does not render the storage device as transitory because the data is not transitory while it is stored.
Computing environment 100 contains an example of an environment for the execution of at least some of the computer code involved in performing the inventive methods, such as a Battery Configuration Control Component 182 and a Battery Type Objective Function Selection Component 184, at block 180. In addition to block 180, computing environment 100 includes, for example, computer 101, wide area network (WAN) 102, end user device (EUD) 103, remote server 104, public cloud 105, and private cloud 106. In this embodiment, computer 101 includes processor set 110 (including processing circuitry 120 and cache 121), communication fabric 111, volatile memory 112, persistent storage 113 (including operating system 122 and block 180, as identified above), peripheral device set 114 (including user interface (UI) device set 123, storage 124, and Internet of Things (IoT) sensor set 125), and network module 115. Remote server 104 includes remote database 130. Public cloud 105 includes gateway 140, cloud orchestration module 141, host physical machine set 142, virtual machine set 143, and container set 144.
COMPUTER 101 may take the form of a desktop computer, laptop computer, tablet computer, smart phone, smart watch or other wearable computer, mainframe computer, quantum computer or any other form of computer or mobile device now known or to be developed in the future that is capable of running a program, accessing a network or querying a database, such as remote database 130. As is well understood in the art of computer technology, and depending upon the technology, performance of a computer-implemented method may be distributed among multiple computers and/or between multiple locations. On the other hand, in this presentation of computing environment 100, detailed discussion is focused on a single computer, specifically computer 101, to keep the presentation as simple as possible. Computer 101 may be located in a cloud, even though it is not shown in a cloud in
PROCESSOR SET 110 includes one, or more, computer processors of any type now known or to be developed in the future. Processing circuitry 120 may be distributed over multiple packages, for example, multiple, coordinated integrated circuit chips. Processing circuitry 120 may implement multiple processor threads and/or multiple processor cores. Cache 121 is memory that is located in the processor chip package(s) and is typically used for data or code that should be available for rapid access by the threads or cores running on processor set 110. Cache memories are typically organized into multiple levels depending upon relative proximity to the processing circuitry. Alternatively, some, or all, of the cache for the processor set may be located “off chip.” In some computing environments, processor set 110 may be designed for working with qubits and performing quantum computing.
Computer readable program instructions are typically loaded onto computer 101 to cause a series of operational steps to be performed by processor set 110 of computer 101 and thereby effect a computer-implemented method, such that the instructions thus executed will instantiate the methods specified in flowcharts and/or narrative descriptions of computer-implemented methods included in this document (collectively referred to as “the inventive methods”). These computer readable program instructions are stored in various types of computer readable storage media, such as cache 121 and the other storage media discussed below. The program instructions, and associated data, are accessed by processor set 110 to control and direct performance of the inventive methods. In computing environment 100, at least some of the instructions for performing the inventive methods may be stored in block 180 in persistent storage 113.
COMMUNICATION FABRIC 111 is the signal conduction path that allows the various components of computer 101 to communicate with each other. Typically, this fabric is made of switches and electrically conductive paths, such as the switches and electrically conductive paths that make up busses, bridges, physical input/output ports and the like. Other types of signal communication paths may be used, such as fiber optic communication paths and/or wireless communication paths.
VOLATILE MEMORY 112 is any type of volatile memory now known or to be developed in the future. Examples include dynamic type random access memory (RAM) or static type RAM. Typically, volatile memory 112 is characterized by random access, but this is not required unless affirmatively indicated. In computer 101, the volatile memory 112 is located in a single package and is internal to computer 101, but, alternatively or additionally, the volatile memory may be distributed over multiple packages and/or located externally with respect to computer 101.
PERSISTENT STORAGE 113 is any form of non-volatile storage for computers that is now known or to be developed in the future. The non-volatility of this storage means that the stored data is maintained regardless of whether power is being supplied to computer 101 and/or directly to persistent storage 113. Persistent storage 113 may be a read only memory (ROM), but typically at least a portion of the persistent storage allows writing of data, deletion of data and re-writing of data. Some familiar forms of persistent storage include magnetic disks and solid state storage devices. Operating system 122 may take several forms, such as various known proprietary operating systems or open source Portable Operating System Interface-type operating systems that employ a kernel. The code included in block 180 typically includes at least some of the computer code involved in performing the inventive methods.
PERIPHERAL DEVICE SET 114 includes the set of peripheral devices of computer 101. Data communication connections between the peripheral devices and the other components of computer 101 may be implemented in various ways, such as Bluetooth connections, Near-Field Communication (NFC) connections, connections made by cables (such as universal serial bus (USB) type cables), insertion-type connections (for example, secure digital (SD) card), connections made through local area communication networks and even connections made through wide area networks such as the internet. In various embodiments, UI device set 123 may include components such as a display screen, speaker, microphone, wearable devices (such as goggles and smart watches), keyboard, mouse, printer, touchpad, game controllers, and haptic devices. Storage 124 is external storage, such as an external hard drive, or insertable storage, such as an SD card. Storage 124 may be persistent and/or volatile. In some embodiments, storage 124 may take the form of a quantum computing storage device for storing data in the form of qubits. In embodiments where computer 101 is required to have a large amount of storage (for example, where computer 101 locally stores and manages a large database) then this storage may be provided by peripheral storage devices designed for storing very large amounts of data, such as a storage area network (SAN) that is shared by multiple, geographically distributed computers. IoT sensor set 125 is made up of sensors that can be used in Internet of Things applications. For example, one sensor may be a thermometer and another sensor may be a motion detector.
NETWORK MODULE 115 is the collection of computer software, hardware, and firmware that allows computer 101 to communicate with other computers through WAN 102. Network module 115 may include hardware, such as modems or Wi-Fi signal transceivers, software for packetizing and/or de-packetizing data for communication network transmission, and/or web browser software for communicating data over the internet. In some embodiments, network control functions and network forwarding functions of network module 115 are performed on the same physical hardware device. In other embodiments (for example, embodiments that utilize software-defined networking (SDN)), the control functions and the forwarding functions of network module 115 are performed on physically separate devices, such that the control functions manage several different network hardware devices. Computer readable program instructions for performing the inventive methods can typically be downloaded to computer 101 from an external computer or external storage device through a network adapter card or network interface included in network module 115.
WAN 102 is any wide area network (for example, the internet) capable of communicating computer data over non-local distances by any technology for communicating computer data, now known or to be developed in the future. In some embodiments, the WAN 102 may be replaced and/or supplemented by local area networks (LANs) designed to communicate data between devices located in a local area, such as a Wi-Fi network. The WAN and/or LANs typically include computer hardware such as copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and edge servers.
END USER DEVICE (EUD) 103 is any computer system that is used and controlled by an end user (for example, a customer of an enterprise that operates computer 101), and may take any of the forms discussed above in connection with computer 101. EUD 103 typically receives helpful and useful data from the operations of computer 101. For example, in a hypothetical case where computer 101 is designed to provide a recommendation to an end user, this recommendation would typically be communicated from network module 115 of computer 101 through WAN 102 to EUD 103. In this way, EUD 103 can display, or otherwise present, the recommendation to an end user. In some embodiments, EUD 103 may be a client device, such as thin client, heavy client, mainframe computer, desktop computer and so on.
REMOTE SERVER 104 is any computer system that serves at least some data and/or functionality to computer 101. Remote server 104 may be controlled and used by the same entity that operates computer 101. Remote server 104 represents the machine(s) that collect and store helpful and useful data for use by other computers, such as computer 101. For example, in a hypothetical case where computer 101 is designed and programmed to provide a recommendation based on historical data, then this historical data may be provided to computer 101 from remote database 130 of remote server 104.
PUBLIC CLOUD 105 is any computer system available for use by multiple entities that provides on-demand availability of computer system resources and/or other computer capabilities, especially data storage (cloud storage) and computing power, without direct active management by the user. Cloud computing typically leverages sharing of resources to achieve coherence and economics of scale. The direct and active management of the computing resources of public cloud 105 is performed by the computer hardware and/or software of cloud orchestration module 141. The computing resources provided by public cloud 105 are typically implemented by virtual computing environments that run on various computers making up the computers of host physical machine set 142, which is the universe of physical computers in and/or available to public cloud 105. The virtual computing environments (VCEs) typically take the form of virtual machines from virtual machine set 143 and/or containers from container set 144. It is understood that these VCEs may be stored as images and may be transferred among and between the various physical machine hosts, either as images or after instantiation of the VCE. Cloud orchestration module 141 manages the transfer and storage of images, deploys new instantiations of VCEs and manages active instantiations of VCE deployments. Gateway 140 is the collection of computer software, hardware, and firmware that allows public cloud 105 to communicate through WAN 102.
Some further explanation of virtualized computing environments (VCEs) will now be provided. VCEs can be stored as “images.” A new active instance of the VCE can be instantiated from the image. Two familiar types of VCEs are virtual machines and containers. A container is a VCE that uses operating-system-level virtualization. This refers to an operating system feature in which the kernel allows the existence of multiple isolated user-space instances, called containers. These isolated user-space instances typically behave as real computers from the point of view of programs running in them. A computer program running on an ordinary operating system can utilize all resources of that computer, such as connected devices, files and folders, network shares, CPU power, and quantifiable hardware capabilities. However, programs running inside a container can only use the contents of the container and devices assigned to the container, a feature which is known as containerization.
PRIVATE CLOUD 106 is similar to public cloud 105, except that the computing resources are only available for use by a single enterprise. While private cloud 106 is depicted as being in communication with WAN 102, in other embodiments a private cloud may be disconnected from the internet entirely and only accessible through a local/private network. A hybrid cloud is a composition of multiple clouds of different types (for example, private, community or public cloud types), often respectively implemented by different vendors. Each of the multiple clouds remains a separate and discrete entity, but the larger hybrid cloud architecture is bound together by standardized or proprietary technology that enables orchestration, management, and/or data/application portability between the multiple constituent clouds. In this embodiment, public cloud 105 and private cloud 106 are both part of a larger hybrid cloud.
Embodiments of the present disclosure provide systems and methods for implementing enhanced operational reliability of battery packs, such as used in computer systems. The disclosed systems and methods optimize battery capacity and extend a functional period for the battery pack, assigning an optimized battery type to each battery cell in the battery pack.
System 200 includes a Battery Pack Reliability Control 201 to implement enhanced operational reliability of one or more Battery Packs 202, e.g., for supplying battery power to computer systems of disclosed embodiments. In this example, each Battery Pack 202 comprises a plurality of battery cells 203, connected together in a linear battery cell string including multiple types of battery cells. For example, each Battery Pack 202 comprises a linear battery cell string of battery cells 203 from a downstream battery cell B1203 proximate to a cooling stream entry point to a distal upstream battery cell BN proximate to a cooling stream exit point. A cooling stream for cooling the battery pack 202 moves from the downstream battery cell B1203 to an upstream battery cell BN, as indicated by an arrow labeled COOLING FLOW. The Battery Packs 202 advantageously can be used with an internal battery feature (IBF) as a local Uninterrupted Power Source (UPS), for example to enhance the robustness of a power design of a mainframe and decrease power line disturbance to mainframe.
System 200 includes a Battery Features Database 204 for storing features and characteristics of each battery cell 203 in the Battery Pack 202 and can store features and characteristics of the Battery Packs 202 of disclosed embodiments. For example, the Battery Features Database 204 can store battery cell selection criteria, such as size, voltage, and battery capacity (types of chemical reaction), and battery cell arrangement options, (e.g., providing locations for battery cells 203 with higher capacity at upstream locations, and lower capacity battery cells at downstream locations in the Battery Packs 202. For example, battery capacities (discharge times) may vary based on ambient temperature in the battery pack 202.
System 200 can access features and characteristics of the Battery Packs 202, such as Inputs 206 comprising, such as T: An array of M different types of battery cells and B: An array of N batteries. System 200 can access Inputs 208, such as X1: graph of temperature versus usable capacity, X2: graph of discharge current versus thermal dissipation, X3: cost of battery (B_cost), X4: other factors affecting battery performance efficiency, X5: temperature gradient versus location in a given battery pack 202 and X6: position of battery in the battery pack. System 200 can access outputs to be optimized such as Outputs 210 Y, such as for each position of battery cells, Battery Bi (i=1 to n), its assignment to one battery type Tj (j=1 to m) of different candidate battery cell types. System 200 can access outputs to be cooled such as Outputs 212 Y2, for each position of battery cell pairs, B_k (k=1, 2; 2,3; . . . n−1,n), its assignment of a cooling mesh structure to selected battery pairs B_k.
System 200 can include the Battery Configuration Control Component 182 and Battery Type Objective Function Selection Component 184. The Battery Configuration Control Component 182 can control example operations of disclosed methods to implement enhanced operational reliability of battery packs 202. The Battery Type Objective Function Selection Component 184 can receive user input of goals to be optimized, such as to minimize the cost of all cells 203 B1-BN while maximizing battery efficiency, and various other parameters that can influence the efficiency of a battery pack 202.
During discharging, testing results indicate the first battery cell B1203 has the lowest increasing rate during the discharging process. The remaining battery cells B1-BN 203 have higher and similar increasing rates of the discharging process and can peak at an ambient temperature of about 68° C. For example, in a battery cell string of N (e.g., 23) battery cells, temperature difference for about the first seven battery cells B1-B7203 may be around 5° C. which is decreasing from upstream to downstream, such as less than 1° C. of the ten cells at downstream. During charging, testing results may indicate that temperatures of all these batteries increase from ambient temperature at 40.5° C. at the beginning of charging process and reach peak temperatures at the end of constant current charging mode at the end of about 1800 seconds. For example, the longest discharging time can occur at ambient temperature of approximately 30° C., which indicates the highest battery capacity under this working condition. Battery capacity decreases when the ambient temperature (ambient T) is higher than 30° C., and the battery capacity decreases more significantly when ambient temperature T is lower, such as close to 0° C. Transient battery temperatures vary along the length of the battery pack 202. The maximum cell surface temperature Ts increases with the increasing of ambient Ts but at a lower increasing rate. In one embodiment, batteries in the battery pack 202 provide equal electric power; however, the battery efficiency increases as the ambient T increases, which contributes to a lower thermal generation rate during the transient discharging process at higher ambient temperature. For example, when a cell surface temperature is in the range of 52-62° C., the battery cell 203 may have the maximum battery discharging time and maximum battery capacity.
System 200 can use the information above to improve the discharge time capacity of the cells B1-BN 203 in the battery pack 202 of disclosed embodiments. For example, system 200 can leverage the temperature gradient along the length of the battery pack 202 to achieve a more uniform discharge profile for the battery pack. Because the surface temperature varies along the length of battery pack, system 200 can assign types of battery cells 203 in the path to maintain surface temperature of all cells to be within an optimal (i.e., selected) range. System 200 can improve discharge capacity of cells 203 by adjusting surface temperature based upon different temperature profiles of different cell types. For example, system 200 can provide various battery arrangements, so that the battery cells 203 can be maintained in the desired temperature range, such as maintaining the battery surface temperature in the range of 52° C.-62° C., to achieve optimized battery capacity. For example, battery pack 202 can be implemented with battery cells 203 having different heat generation values, such as battery cells 203 B1-B15 implemented with a 2.0 W battery cell type, battery cells 203 B6-B19 implemented with a 1.8 W cell type, and battery cells 203 B20-B23 implemented with a 1.5 W cell type. System 200 can use various commercially available types of battery cells 203, each having a same size and voltage and different battery capacity (e.g., types of chemical reaction). System 200 can selectively provide battery cells with higher capacity at the upstream cooling flow locations, and lower capacity battery cells at downstream locations. System 200 can selectively install a heat removal porous metal mesh structure in contact engagement with one or more selected battery cells 203 at selected battery locations in the linear battery cell string of the battery pack to optimize battery cell capacity and maintain a selected temperature range for the selected battery cells.
The Battery Configuration Control Component 182 and Battery Type Objective Function Selection Component 184 for example are used together with the computer 101 and cloud environment of the computing environment 100 of
At block 310, system 200 can formulate an Integer Linear Problem (ILP). In Integer linear programming, an objective function and the constraints (other than the integer constraints) are linear. At block 312, system 200 can solve the ILP using traditional techniques, for example to minimize an objective function. At block 312, system 200 can obtain feasible solutions for selection of battery types Tj (j=1 to m) of battery cells 203 for each battery Bi (i=1+n) in the linear string of battery cells 203, to provide enhanced operational reliability of battery packs 202 of disclosed embodiments. At block 314, system 200 assigns battery type Tj to each battery cell Bi 203 in the battery pack 202 and operations end at block 316.
System 200 can implement the integer linear problem formulated at block 310 in
Alternatively system 200 performs operations at block 504 instead of the above described operation of block 502. At block 504, system 200 sequentially replaces respective selected numbers of cells (n1, n2, nn) for each of the respective different types (m1, m2, mn) of battery cells starting from upstream battery cells (e.g., battery cells 203 BN-3, BN-2, BN-1, and BN) in the battery pack linear cell string. For example at block 504, by selectively replacing selected battery cells (respective upstream cells (n1, n2, nn) with respective different cell types (m1, m2, mn), average battery cell temperatures can be reduced, to improve average operation for battery pack 202. At block 506, system 200, the battery cell type Tj, such as assigned at block 314 in
At block 604, system 200 determines, for each position of the battery cells in the linear cell string, battery parameters for each of the different candidate cell types. For example, system 200 can determine the battery parameters, for each battery position and each battery type, comprising one or more of computed battery temperature, computed battery usable capacity, computed battery efficiency and other selected battery parameters. As discussed above, the battery parameters for the different candidate cell types can vary depending on the position that the battery cell is located in the linear cell string. For example, the battery temperature for a cell type can vary depending on whether it is at the front of the string (where cooling is greater) or at the end of the string.
At block 606, system 200 formulates an integer linear problem to optimize a battery configuration for the battery pack based on the calculated battery parameters for each position of the plurality of battery cells. For example, system 200 models the integer linear problem as a multi-constrained optimization problem, defining an objective function based on selected battery parameters for each battery cell. At block 608, system 200 solves the integer linear problem to select, one of the different candidate battery types to place at each of the positions of the battery cells in the linear cell string. Operations end as indicated at block 610.
In disclosed embodiments, a metal structure having high thermal conductivity, such as a metal mesh structure is selectively provided to be positioned in contact engagement with selected battery cells. One or more metal mesh structures are selectively provided to compensate for a difference in surface temperature of battery cells at identified position in the linear battery cell string of the battery pack, to provide optimal battery cell capacity with a more uniform surface temperature of all the battery cells. The surface temperature of battery cells can vary by position of battery cells, with some battery cells at some positions having a lower surface temperature than other battery cells. For example, the metal mesh structure can be positioned with selected pairs of battery cells to maintain in a desired surface temperature range for the selected battery cells, to achieve optimal battery capacity. In disclosed embodiments, the cooling metal mesh structure is configured to minimize flow impedance to a cooling flow path of the battery pack, while minimizing a battery cell surface temperature gradients of the linear battery cell string of the battery pack. In one embodiment, the cooling porous metal mesh structure is formed of an Aluminum or Copper cylindrical mesh structure. The cylindrical metal mesh structure is readily deformable, enabling battery pack installation and removal for example for battery cell servicing.
At block 706, system 200 assigns a cooling mesh structure for the selected battery cell positions, for example to reduce the battery cell surface temperature gradient of the battery cells. At block 708, system 200 can provides the battery pack 202 with example cooling metal mesh structures to be selectively installed in contact engagement with selected battery cells at the selected battery cell positions. The installed cooling metal mesh structure can provide enhanced discharge capacity of the battery cells by adjusting the surface temperature of the selected battery cells at selected positions. The installed cooling metal mesh structure can effectively minimize temperature gradients for the battery cells at the identified positions in the battery pack 202. Operations end at block 710.
In disclosed embodiments, the cooling mesh structure has a selected configuration to provide effective cooling performance and minimize flow impedance to the cooling flow path of the battery pack 202. For example, the assigned cooling mesh structures can minimize a battery cell surface temperature gradient of associated battery cells, and fit into an existing design structure for the battery pack, without requiring modification or addition of extra structure. Each cooling mesh structure provides additional surface area of cooling for the battery pack 202 and improve overall discharge capacity of battery pack.
In disclosed embodiments, both cooling mesh structures 800 and 820 can provide additional cooling for battery packs 202 to minimize battery cell surface temperature gradients of associated battery cells 203 at identified positions to improve overall discharge capacity of battery pack. The cooling mesh structures 800 and 820 are deformable structures, (e.g., compressible structures), formed of a selected flexible metal mesh material. The cooling mesh structures 800 and 820 are formed of a selected flexible metal mesh material having high thermal conductivity, such as Aluminum (Al)), Copper (Cu), and the like. The cooling mesh structures 800 and 820 are deformable, providing flexibility to enable installation and removal of battery packs 202, such as for battery servicing. A height of the metal mesh members can be about the same height as the associated battery cells 203. A diameter of the metal mesh forming the cooling mesh structures 800 and 820 is selectively provided based on an available empty space to receive the cooling mesh structures, between a PCB and at selected positions of the battery cells 203 of the battery pack 202. For example, the metal mesh diameter can be in a range between 5 mm and 50 mm and a selected metal mesh thickness can be in a range between 1 mm and 8 mm.
In a disclosed embodiment, the cylindrical cooling mesh structure 902 includes multiple mesh layers, as shown in the top plan view of
Either of the cooling metal mesh structures 902 and 904 can be selectively used at assigned battery cell positions in the linear battery cell string of battery packs 202 to provide additional cooling for battery packs, for example based on cooling requirements of battery cell pair 203 Bk at the identified battery positions in the battery packs 202. For example, one of the cooling metal mesh structures 902 or 904 can be selected for use at identified battery pair positions based on available space with a given battery pack 202.
For example, the cooling mesh structures 902 and 904 can be installed to fit into an available empty space or gap in the existing battery rack chassis (not shown in
For example, the cooling mesh structures 902 and 904 can be fixedly mounted to selected battery cells 203 as respectively indicated at 902A, 902B, and 904A, 904B. A selected glue or adhesive Thermal Interface Material (TIM) can be used fixedly attach or secure the cooling mesh structures 902 and 904 to the battery cells 203.
Alternatively, the cooling mesh structures 902 and 904 can be mounted to an available supporting printed circuit board (PCB) 910, as respectively indicated at 902C and 904C. The PCB 910 is spaced apart from the battery cells 203 Bk in an enclosure or chassis, for example containing multiple parallel battery packs 202. The cooling mesh structures 902 and 904 can be fixedly secured to the PCB 910, such as by soldering or using selected glue.
In the partial insertion position 920 of
In the operational insertion position 930 of
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
