Coolant distribution unit control system

Abstract

A coolant distribution unit control system is provided. Specifically, a coolant distribution unit ("CDU") and a method of operating a component of the CDU are provided, the method comprising: detecting a fault of the component based on first sensor information from a first sensor of a plurality of sensors of the CDU; receiving second sensor information corresponding to the component from a second sensor of the plurality of sensors; verifying whether the fault is valid based on the second sensor information; and continuing operation of the component in response to determining that the fault is invalid.

Description

[0001] Cross-reference to related applications: This application claims priority to co-pending U.S. Provisional Patent Application No. 63 / 709,257, filed October 18, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure generally relates to a coolant distribution unit control system, and more particularly to a method for operating components of a coolant distribution unit, a method for controlling a coolant distribution unit, and a coolant distribution unit. Background Technology

[0003] Computer systems / data centers employ various cooling / heat dissipation methods to maintain environmental conditions suitable for the operation of information technology (IT) equipment, such as servers, network switches, routers, storage devices, and other computing hardware. Some data centers may utilize liquid cooling systems, where a liquid coolant is used to absorb heat generated from high-power equipment.

[0004] The liquid cooling system includes one or more coolant distribution units (CDUs) configured to actively distribute liquid coolant to various components within a data center. Each CDU includes a primary flow loop / return and a secondary flow loop / return. The primary flow loop / return is configured to supply liquid coolant to the heat-absorbing side of a heat exchange technology (e.g., a liquid-to-liquid heat exchanger) located within or outside the CDU itself. The secondary flow loop / return is configured to receive heated (“used”) liquid coolant at the heat-dissipating side of the heat exchange technology and return cooled liquid coolant to the equipment's liquid cooling network. Within the cooling network of the secondary flow loop, liquid coolant is supplied via one or more feed lines to cooling modules (e.g., single or series of cooling plates or radiators) near or within the IT equipment, absorbing heat from the equipment through these feed lines. The heated liquid coolant then flows through one or more return feed lines across the heat-dissipating side of the heat exchange technology within or outside the CDU, thereby dissipating heat from the liquid coolant. The cooled liquid coolant is then circulated back to the information technology equipment via one or more feed lines.

[0005] Within the primary flow loop, the used liquid coolant from the heat exchange technology is cooled by one or more secondary cooling methods (e.g., a chiller, cooling towers, etc.). The cooled liquid coolant is then recirculated back through the heat dissipation side of the heat exchange technology.

[0006] The Cooling Duct (CDU) operates via a pump system that circulates liquid coolant through a network of pipes or channels. The CDU integrates additional components such as valves, filters, and monitoring mechanisms to optimize cooling efficiency and system reliability. Precisely calibrated valves allow for dynamic coolant distribution adjustments tailored to the needs of individual equipment / components, while filters (e.g., within the primary flow loop) remove impurities and contaminants. Equipped with sensors, the CDU continuously monitors coolant parameters such as temperature, flow rate, and pressure levels, enabling real-time intervention to maintain peak thermal performance and reliability in complex environments.

[0007] For larger data centers, reliable CDU operation can be critical to prevent overheating and ensure equipment performance and lifespan. Therefore, the embodiments described herein provide various control methods and systems for CDU fault detection and mitigation. Summary of the Invention

[0008] Therefore, in one aspect, this disclosure provides a method for operating a component of a cooling distribution unit (CDU), the method comprising: detecting a fault in the component based on first sensor information from a first sensor among a plurality of sensors of the CDU; receiving second sensor information corresponding to the component from a second sensor among the plurality of sensors; verifying whether the fault is valid based on the second sensor information; and continuing operation of the component in response to determining that the fault is invalid.

[0009] In another aspect, this disclosure provides a method for controlling a coolant distribution unit (CDU), the method comprising: determining the operating condition of a component of the CDU; determining a desired value of a sensor configured to measure the condition of the component; and comparing the desired value with an actual value measured by the sensor.

[0010] In another aspect, this disclosure provides a coolant distribution unit comprising: a fluid coolant flow system including one or more components; a controller configured to control the operation of the components; a first sensor configured to provide first sensor information based on a first condition of the fluid coolant flow system; a second sensor configured to provide second sensor information based on a second condition of the fluid coolant flow system; and a third sensor configured to provide third sensor information based on a third condition of the fluid coolant flow system, wherein the controller is configured to determine a fault in the component based on either the first or second sensor information, verify whether the fault is valid based on the other sensor information between the first and second sensor information, and continue operation of the component in response to determining that the fault is invalid, and determine an expected value of the third sensor based on the operating condition of one of the components, and compare the expected value with the third sensor information. Attached Figure Description

[0011] Figure 1A A coolant distribution unit (CDU) according to some embodiments is shown.

[0012] Figure 1B Illustrations are shown according to some embodiments Figure 1A CDU.

[0013] Figure 2A According to some embodiments Figure 1A The first part of the schematic diagram of the liquid coolant system of the CDU.

[0014] Figure 2B According to some embodiments Figure 2A The second part of the schematic diagram of the liquid coolant system.

[0015] Figure 3 This is a block diagram of an electronic controller for a CDU according to some embodiments.

[0016] Figure 4 Illustrations are shown according to some embodiments Figure 1A The equipment cooling network and CDU.

[0017] Figure 5 It is based on some embodiments of the invention. Figure 3 The electronic controller is used for operation Figure 1A A flowchart of the method for the components of the CDU.

[0018] Figure 6 It is based on some embodiments of the invention. Figure 3 The operation implemented by the electrical controller Figure 1A A flowchart of the method for the components of the CDU. Detailed Implementation

[0019] The embodiments described herein relate to a coolant distribution unit (CDU).

[0020] Before explaining any embodiment in detail, it should be understood that the application of the embodiments is not limited to the details of the configuration and arrangement of the components set forth in the following description or shown in the accompanying drawings. Embodiments can be practiced or performed in various ways. Moreover, it should be understood that the wording and terminology used herein are for descriptive purposes and should not be considered limiting. The use of “comprising,” “including,” or “having,” and variations thereof is intended to cover the items listed thereafter and their equivalents, as well as additional items. Unless otherwise stated or limited, the terms “installation,” “connection,” “support,” and “linkage,” and variations thereof are used extensively and cover direct and indirect installation, connection, support, and linking.

[0021] Additionally, it should be understood that embodiments may include hardware, software, and electronic components or modules, which, for the purposes of discussion, may be shown and described as if most components were implemented solely in hardware. However, those skilled in the art, and based on this detailed description, will recognize that in at least one embodiment, the electronic aspects may be implemented in software (e.g., stored on a non-transitory computer-readable medium) capable of being executed by one or more processing units (e.g., microprocessors and / or application-specific integrated circuits (“ASICs”)). Therefore, it should be noted that embodiments may be implemented using multiple hardware and software-based devices and multiple different structural components. For example, “server,” “computing device,” “controller,” “processor,” etc., described in the specification may include one or more processing units, one or more computer-readable medium modules, one or more input / output interfaces, and various connectors (e.g., system buses) for connecting components.

[0022] Relative terms used in conjunction with quantities or conditions, such as “about,” “approximately,” “substantially,” etc., will be understood by those skilled in the art to include the stated value and have a meaning indicated by the context (e.g., the term includes at least the degree of error associated with measurement accuracy, the tolerance associated with a particular value [e.g., manufacturing tolerance, assembly tolerance, usage tolerance, etc.]). Such terms should also be considered to disclose a range defined by the absolute values ​​of the two endpoints. For example, expressing “from about 2 to about 4” also discloses the range “from 2 to 4.” Relative terms may indicate the indicated value plus or minus a certain percentage (e.g., 1%, 5%, 10% or more).

[0023] It should be understood that although some of the accompanying figures show hardware and software located within a particular device, these depictions are for illustrative purposes only. Functions described herein as being performed by one component can be performed by multiple components in a distributed manner. Similarly, functions performed by multiple components can be combined and performed by a single component. In some embodiments, the components shown can be combined or divided into separate software, firmware, and / or hardware. For example, instead of being located within and performed by a single electronic processor, logic and processing can be distributed among multiple electronic processors. Regardless of how they are combined or divided, hardware and software components can reside on the same computing device or can be distributed among different computing devices connected by one or more networks or other suitable communication links. Similarly, components described as performing specific functions can also perform additional functions not described herein. For example, a device or structure "configured" in a certain way is configured at least in this manner, but can also be configured in a way not explicitly listed.

[0024] For ease of description, some or all of the example systems presented herein are illustrated using a single example of each of their component sections. Some examples may not describe or show all the components of the system. Other examples may include more or fewer of each of the components shown, may combine some components, or may include additional or alternative components.

[0025] Other aspects of the embodiments will become apparent from consideration of the detailed description and accompanying drawings.

[0026] Figure 1A and Figure 1B An exemplary coolant distribution unit (CDU) 100 is shown. The CDU 100 particularly includes an electronic controller 300 (described below). Figure 3 (Described in more detail), multiple pumps (e.g., fill and replenishment pump 102, variable frequency drive (VFD) pump 104, and secondary pump 106), multiple valves (e.g., primary control valve 108, pump check valve 110, isolation valve 112), and multiple sensors (e.g., temperature sensor 114, pressure sensor 116, flow meter 118). The CDU 100 also includes a reservoir 120, an expansion tank 122, and a liquid-liquid heat exchanger 124. The CDU also includes a housing (not shown).

[0027] Figures 2A to 2B This is a schematic diagram illustrating a fluid coolant flow system 200 of a CDU 100 according to some embodiments. System 200 includes a primary fluid flow path (referred to herein as primary loop 202A) for liquid coolant on a first (heat absorption) side of heat exchanger 124 and a secondary flow path (referred herein as secondary loop 202B) for liquid coolant on a second (heat dissipation) side of heat exchanger 124. Primary loop 202A includes an inlet valve J3 and an outlet valve J2 (… Figure 1A and Figure 1B Isolation valve 112). Secondary circuit 202B includes input valve J1 and output valve J4 ( Figure 1A and Figure 1B (Isolation valve 112). Heat exchanger 124 receives cooled liquid coolant from primary circuit 202A to dissipate heat from the liquid coolant received in secondary circuit 202B on the heat-absorbing side of heat exchanger 124. The cooled liquid coolant in secondary circuit 202B is then (at valve J4) output (e.g., output to equipment coolant network 400, as discussed below). Figure 4 The description describes a system 400 whereby a recirculated coolant is provided for cooling one or more information technology (IT) devices, such as servers, network switches, routers, storage devices, and other computing hardware. Heated liquid coolant from network 400 is then returned to system 200 (at valve J1). Simultaneously, heated liquid coolant in primary circuit 202A is recirculated and cooled (e.g., via a secondary cooling / heat transfer system (not shown) that receives the heated liquid coolant output at valve J2 and provides cooled liquid coolant back to CDU 100 at the input of valve J3). In some embodiments, CDU 100 may include additional components / subsystems for additional cooling of the liquid coolant.

[0028] Figure 4 This is an example device cooling network 400 for cooling multiple IT devices according to some embodiments. The device cooling network 400 includes a feed line 402A configured to receive a cooled liquid coolant output from CDU 100 (i.e., Figure 2B (Output of valve J4). Feed line 402A is connected to one or more secondary pipes (not shown) of equipment racks / housings 404, each of which includes one or more IT devices. The secondary pipes of racks / housings 404 may extend along one or more heat transfer surfaces of racks / housings 404 (or the IT devices themselves) to absorb heat generated from the respective IT devices. From each rack / housing 404, the heated coolant returns to CDU 100 (in) via return line 402B. Figure 2B (At the input of valve J3) to recool and recirculate within the equipment cooling network 400.

[0029] Return to Figures 2A to 2BAs shown in the figure, the primary circuit 202A includes multiple valves V17, V19, J2, and J3, and sensors (e.g., temperature sensors T4 and T5, pressure sensors P10, P12, and P13, and flow meter FM1). The secondary circuit 202B also includes multiple valves V1-V16, V18, V20, J1, and J4, pumps PMP1-PMP4, and sensors (e.g., temperature sensors T1-T3 and T6-T8, pressure sensors P1-P9, P11, and P14, and flow meter FM2). The controller 300 is communicatively connected to each of the aforementioned multiple valves V1-V20 and pumps PMP1-PMP4, and controls the operation of each of the aforementioned multiple valves V1-V20 and pumps PMP1-PMP4 based on sensor information from one or more of the various sensors from the system 200. The controller 300 can also receive sensor information about the environment inside the housing of the CDU 100 (e.g., via a relative humidity sensor RH1 and an ambient temperature sensor T9) and sensor information about the environment outside the housing of the CDU 100 (e.g., via a relative humidity sensor RH2 and a temperature sensor T10). For ease of description, the sensors of the flow system 200 are collectively referred to herein as a plurality of sensors 204, the valves of the flow system 200 are collectively referred to herein as a plurality of valves 206, and the pumps of the flow system 200 are collectively referred to herein as a plurality of pumps 208. In some embodiments, one or more different types of sensors (and their functions) of the system 200 may be combined into a single sensor (e.g., a combination of temperature and humidity sensors, a combination of pressure and water flow sensors, etc.). The system 200 may include more than Figures 2A to 2B The number of sensors shown may be more or less.

[0030] The fluid coolant flow system 200 may include additional components (e.g., filters FIL1-FIL3, screens ST1-ST4, automatic vents, and pressure relief valves), which will not be described in detail here for the sake of brevity.

[0031] Figure 3This is a block diagram of an electronic controller 300 of a CDU 100 according to some embodiments. The electronic controller 300 includes a plurality of electrical and electronic components that facilitate power supply, operational control, and protection of components and modules within the electronic controller 300. The electronic controller 300 particularly includes an electronic processor 305 (such as a programmable electronic microprocessor, microcontroller, or similar device), a memory 310 (e.g., a non-transitory computer-readable memory), and an input / output interface 315. The electronic processor 305 is communicatively connected to the memory 310 and the input / output interface 315. The electronic processor 305, together with the memory 310 and the input / output interface 315, is configured to implement, in particular, the methods described herein. It should be understood that some or all components of the controller 300 (including additional components) may be remote / dispersed from each other and / or located away from the CDU 100 within the CDU 100.

[0032] The memory 310 may consist of one or more non-transitory computer-readable media and includes at least a program storage area and a data storage area. The program storage area and the data storage area may include combinations of different types of memory, such as read-only memory (“ROM”), random access memory (“RAM”), flash memory, or other suitable memory devices. An electronic processor 305 is coupled to the memory 310 and the input / output interface 315.

[0033] Electronic processor 305 (e.g., from memory 310 and / or input / output interface 315) sends and receives information and processes this information by executing one or more software instructions or modules that can be stored in memory 310 or another non-transitory computer-readable medium. The software may include firmware, one or more applications, program data, filters, rules, one or more program modules, and other executable instructions. Electronic processor 305 is configured to retrieve from memory 310 and, in particular, execute software for automatically detecting / predicting anomalies within CDU 100 and for performing the methods described herein.

[0034] In some cases, the electronic controller 300 may be implemented in several independent controllers (e.g., programmable electronic controllers), each configured to perform a specific function or sub-function. For example, one or more components of the controller 300 may be located remotely from the CDU 100 (e.g., part of a remote server, not shown, communicatively connected to the CDU 100). Additionally, the electronic controller 300 may include submodules comprising additional electronic processors, memories, or circuitry for handling input / output functions, signal processing, and applying the methods listed below. In other cases, the electronic controller 300 includes additional, fewer, or different components. Therefore, the program may also be distributed among one or more processors.

[0035] Input / output interface 315 transmits and receives information from devices external to electronic controller 300 (e.g., via one or more wired and / or wireless connections), such as components of CDU 100. Input / output interface 315 receives input from multiple sensors 204 and provides system output to multiple valves 206 and / or one or more pumps 208, transceiver 325 and / or human-machine interface 330 (“HMI”), etc. Input / output interface 315 may also include other input and output mechanisms, which are not described herein for brevity, and may be implemented in hardware, software, or a combination of both.

[0036] In some cases, the controller 300 also includes a transceiver 325 and / or an HMI 330. The transceiver 325 includes a radio transceiver that transmits data over one or more wireless communication networks (e.g., cellular networks, satellite networks, terrestrial mobile radio networks, etc.). The transceiver 325 also provides in-vehicle wireless communication using appropriate network modes (e.g., Bluetooth™, Near Field Communication (NFC), Wi-Fi™, etc.). Therefore, the transceiver 325 communicatively connects the electronic controller 300 and other components of the CDU 100 to networks or electronic devices internal to and external to the CDU 100. For example, the electronic controller 300 can use the transceiver 325 to communicate with one or more devices (e.g., other CDU 100s) via a communication system (not shown) to send and receive data, commands, and other information. The transceiver 325 includes other components for implementing wireless communication (e.g., amplifiers, antennas, baseband processors, etc.), which are not described herein for brevity and can be implemented in hardware, software, or a combination of both. Some instances involve multiple transceivers or separate transmit and receive components (e.g., transmitter and receiver) rather than a combined transceiver.

[0037] The HMI 330 provides visual output, such as graphic indicators (i.e., fixed or animated icons), lights, colors, text, images, and combinations thereof. The HMI 330 includes suitable display mechanisms for displaying the visual output, such as instrument clusters, center console displays (e.g., touchscreens or other suitable mechanisms), etc. In some cases, the HMI 330 displays a graphical user interface (GUI) that allows the driver or passenger to interact with the CDU 100 (e.g., generated by the electronic processor 305 and presented on a display screen). The HMI 330 may also provide audio output to the driver via speakers included in or separate from the HMI 330, such as ringtones, buzzers, voice outputs, or other suitable sounds. In some cases, the HMI 330 provides a combination of visual and audio output.

[0038] As will be described in further detail below, in some cases, memory 310 includes, in particular, computer-executable instructions for component and measurement fault detection and mitigation. In some cases, the computer-executable instructions include instructions for training a deep learning system to detect / predict one or more anomalies associated with one or more components of CDU 100.

[0039] In some cases, the electronic controller 300 uses one or more machine learning methods (e.g., artificial intelligence algorithms) to analyze sensor information from sensor 204 to identify / predict anomalies within CDU 100 (as described herein). Machine learning generally refers to the ability of a computer program to learn without being explicitly programmed. In some cases, the computer program (e.g., a learning engine) is configured to build algorithms based on inputs. Supervised learning involves presenting a computer program with example inputs and their expected outputs. The computer program is configured to learn general rules that map inputs to outputs based on the training data it receives. Example machine learning engines include decision tree learning, association rule learning, artificial neural networks, classifiers, edge computing, inductive logic programming, support vector machines, clustering, Bayesian networks, reinforcement learning, representation learning, similarity and metric learning, sparse dictionary learning, and genetic algorithms. Using these methods, the computer program can ingest, parse, and understand data and progressively refine algorithms for data analysis.

[0040] The system performance of the flow system 200 is particularly dependent on the proper operation of the pumps 208. In some embodiments, each pump includes a corresponding pump fault sensor (e.g., a fault sensor integrated into the pump). When the pump fault sensor indicates a fault, the sensor is configured to provide a fault signal to the electronic controller 300. In response, the electronic controller 300 may accordingly generate an alarm to the user (e.g., via HMI 330), stop or adjust the operation of one or more pumps in the pumps 208, or both. However, there may be cases where the pump fault sensor itself is faulty. In such cases, the pump fault sensor may output a fault signal to the controller 300 even when the corresponding pump is operating normally. This may cause the controller 300 to provide false alarms and / or unnecessary modifications / shutdowns to one or more operations of the system 200.

[0041] Therefore, it may be expected that the electronic controller 300 performs additional steps to verify that one or more pumps in the pump are operating correctly, including assessing the accuracy of measurements from one or more sensors in the sensor 204.

[0042] Figure 5This is a flowchart of a method 500 for operating components (e.g., pumps) of CDU 100 according to some embodiments. Although method 500 is described in conjunction with a pump of CDU 100 as described herein, method 500 can be used with other types of components of the CDU (e.g., valves in the plurality of valves 206). Furthermore, method 500 can be modified or performed differently from the specific example provided. As an example, method 500 is described as being performed by electronic controller 300 and specifically by electronic processor 305. However, it should be understood that in some cases, portions of method 500 can be performed by other devices or subsystems of CDU 100. For ease of description, the method is described with respect to a single pump in the plurality of pumps 208 and a single first and second sensor. However, it should be understood that method 500 can be implemented for more than one component of CDU 100 (e.g., more than one pump in pumps 208) and more than one first and / or second sensor.

[0043] At block 502, electronic processor 305 detects a (potential) fault in a component based on first sensor information from a first sensor among a plurality of sensors 204. The first sensor may be, for example, a pump sensor, and the first sensor information may be a pump fault signal. At block 504, electronic processor 305 receives second sensor information corresponding to the component from a second sensor among the plurality of sensors 204. In some embodiments, the second sensor information comes from more than one of the plurality of sensors 204. The second sensor information may be information from one or more sensors upstream of the component and / or the first sensor, downstream of the component and / or the first sensor, or both. As another example, the second sensor may include a specific sensor selected by electronic controller 300 based on the specific component being analyzed (e.g., based on the component's location within system 200). The second sensor information may be from a common type of sensor (e.g., a temperature sensor, a pressure sensor, etc.) or from more than one type of sensor. In some embodiments, the type of sensor providing sensor information to processor 305 is not the same as the type of sensor as the first sensor. For example, in some embodiments, the first sensor is a flow sensor, and one or more other sensors are pressure sensors.

[0044] At block 506, electronic processor 305 verifies whether a fault in the component is valid based on the second sensor information. For example, if pump 208 is not operational at block 506, a fault can be determined to be valid. In response to determining that the fault is valid, electronic processor 305 performs a fault mitigation action at block 508 (e.g., generating an alarm to the user (e.g., via HMI 330), adjusting the operation of one or more components of CDU 100, etc.). If electronic processor 305 determines that the fault is invalid at block 506, electronic processor 305 receives the second sensor information at block 510. In other embodiments, the electronic processor may receive third sensor information from another of a plurality of sensors. The third sensor and the third sensor information may be the same as the second sensor and the second sensor information, respectively, or they may be different sensors and different sensor information. In response to determining that the fault is invalid, electronic processor 305 determines whether to continue allowing the component to operate (block 512), ignore the first sensor information (and the detected potential fault) and continue operating the component (block 514), or not allow the component to operate and perform a fault mitigation action (block 508). In some embodiments, at block 508, the electronic processor 305 is also configured to generate an alert to the user regarding a potential malfunction of the first sensor.

[0045] refer to Figure 6In some embodiments, controller 300 is configured to operate one or more pumps 208, one or more valves 206, or both, according to feedforward loop 600. Feedforward loop method 600 is described as being performed by electronic controller 300. However, it should be understood that in some cases, portions of method 600 may be performed by other devices or subsystems of CDU 100. For a given operation of one or more components of system 200, controller 300 may be configured to determine and / or set one or more operating conditions of the component at a first step 602. Operating conditions may be, for example, desired operating conditions, such as desired flow rate, desired coolant temperature, etc. For example, controller 300 may operate at the pump at 60% of the pump's maximum speed, which is the operating condition determined by controller 300. At a second step 604, based on the operating conditions, controller 300 is configured to determine one or more desired values / ranges of values ​​for one or more sensors 204. For example, when a particular pump among multiple pumps 208 is operated at 60% of its maximum speed, the controller 300 determines one or more desired values ​​(e.g., temperature, pressure, flow, etc.) from one or more of multiple sensors 204 (e.g., temperature sensors, pressure sensors, flow sensors, etc.). The desired values ​​may be predetermined and stored, for example, in memory 310 (e.g., in a lookup table), generated from one or more performance prediction models, or some combination thereof. At a third step 606, the controller 300 compares the desired value / range determined at step 604 with measurements of the condition from the sensor 204. In some embodiments, a feedforward loop may be used for more efficient operation of the CDU and / or optimization to enhance energy consumption and reliability. For example, the feedforward loop may determine a desired operating condition (e.g., an energy-efficient desired motor speed) at step 602, then determine a desired value based on that operating condition, and compare that desired value with the condition measured by the sensor. In this process, the controller 300 is able to more accurately predict the operating condition measured by the sensor based on another desired condition. In this way, the controller 300 can also operate under desired operating conditions, rather than gradually increasing, for example, the motor speed, to achieve the desired operating conditions, which is faster and more efficient. In the following steps, the controller 300 can further refine the operating conditions (e.g., modify the pump speed) to change the operating conditions measured by the CDU 100.

[0046] As mentioned above, erroneous fault detection can impair the system performance of the CDU. Such erroneous fault detection may be caused by inaccurate measurements and / or faulty sensors. Therefore, it may be advantageous to verify the measurements from the sensors by comparing measurements from multiple (redundant) sensors of a common type located nearby to determine if any sensors are inaccurate. This can be beneficial for components with a limited number of sensor measurements. For example, the VFD pump 208 may include a single input for receiving pressure measurements. In this case, it is important that the received measurement is accurate.

[0047] In some embodiments, the electronic controller 300 (and its components) is mounted on a single circuit board.

Claims

1. A method of operating a component of a cooling distribution unit (CDU), the method comprising: The component fault is detected based on the first sensor information from the first sensor among multiple sensors of the CDU; Receive second sensor information corresponding to the component from the second sensor among the plurality of sensors; Based on the information from the second sensor, verify whether the fault is valid; as well as In response to determining that the fault is invalid, operation of the component continues.

2. The method according to claim 1, wherein, The first sensor and the second sensor are one of a temperature sensor, a pressure sensor, and a flow meter.

3. The method according to claim 1, wherein, The component in question is a pump.

4. The method according to claim 1, wherein, The component in question is a filter.

5. The method according to claim 1, wherein, The first sensor information and the second sensor information correspond to the temperature of the coolant.

6. The method according to claim 1, wherein, The first sensor information and the second sensor information correspond to the flow rate of the coolant.

7. The method according to claim 1, wherein, The first sensor information and the second sensor information correspond to the pressure of the coolant.

8. A method for controlling a coolant distribution unit (CDU), the method comprising: Determine the operational status of the components of the CDU; Determine the desired value for the sensor, which is configured to measure the condition of the component; as well as The expected value is compared with the actual value measured by the sensor.

9. The method according to claim 8, wherein, The expected value is stored in memory.

10. The method according to claim 8, wherein, The component is one of a pump and a valve.

11. The method according to claim 8, wherein, The operating condition is one of flow rate, temperature, or pressure.

12. A coolant distribution unit, comprising: A fluid coolant flow system, the fluid coolant flow system comprising one or more components; A controller, configured to control the operation of the component; as well as A first sensor, configured to provide first sensor information based on a first condition of the fluid coolant flow system; a second sensor, configured to provide second sensor information based on a second condition of the fluid coolant flow system; and a third sensor, configured to provide third sensor information based on a third condition of the fluid coolant flow system. The controller is configured to: Based on the information from the first sensor or the second sensor, the fault of the component is determined. Based on the information from the first sensor and the information from the second sensor, verify whether the fault is valid, and In response to determining that the fault is invalid, operation of the component continues, and Based on the operational status of one of the components, the expected value of the third sensor is determined, and The expected value is compared with the information from the third sensor.

13. The coolant distribution unit according to claim 12, wherein, The first sensor and the second sensor are one of a temperature sensor, a pressure sensor, and a flow meter.

14. The coolant distribution unit according to claim 12, wherein, The components include one of a pump and a filter.

15. The coolant distribution unit according to claim 12, wherein, The first sensor information and the second sensor information correspond to the temperature of the coolant.

16. The coolant distribution unit according to claim 12, wherein, The first sensor information and the second sensor information correspond to the flow rate of the coolant.

17. The coolant distribution unit according to claim 12, wherein, The first sensor information and the second sensor information correspond to the pressure of the coolant.

18. The coolant distribution unit according to claim 12, wherein, The third sensor is the same as the second sensor.

19. The coolant distribution unit according to claim 12, wherein, The expected value is stored in memory.

20. The coolant distribution unit according to claim 12, wherein, The third sensor is one of a flow sensor, a pressure sensor, and a temperature sensor.

Images