A cooling device based on thermal network model and control method thereof

Abstract

The present disclosure provides a cooling device based on a thermal network model and a control method thereof. The device is used to cool a load, and the device includes: a coolant storage device for storing coolant; a coolant valve connected to the load and a preset position in the load's driver, for providing a corresponding amount of coolant to the preset position to cool the preset position; a controller for: building a thermal network model based on real-time operating parameters of the load and the driver to determine the current amount of coolant required for the preset position; and / or, predicting the working condition of the load in a preset time period based on the real-time operating parameters, obtaining the predicted working condition, so as to obtain the predicted amount of coolant corresponding to the preset position; and controlling the amount of coolant provided to the preset position by the coolant valve based on the current amount and / or the predicted amount.

Description

Technical Field

[0001] The present disclosure relates to the field of motors, and in particular to a cooling device based on a thermal network model and a control method thereof. Background Art

[0002] High-power-density electric drive systems can significantly reduce vehicle cost and weight, greatly improve the power system of new energy traction devices, and comprehensively enhance the efficiency and safety of new energy traction devices. However, there are permanent magnet motors inside high-power-density electric drive systems. When the temperature is too high, it is easy to cause irreversible demagnetization of the permanent magnets, which will affect the smooth and safe operation of new energy traction devices.

[0003] Oil-cooled flat-wire motors are usually used in electric drive systems, and the cooling flow control of their cooling systems is basically approximately constant. For safety reasons, there is a certain margin on the basis of meeting the internal motor peak power operation heat dissipation, which can fully meet the internal cooling needs of the drive system. However, the existing cooling system cannot monitor and predict the temperature of key parts inside the electric drive system, resulting in low cooling efficiency and accuracy. Summary of the invention

[0004] The present disclosure proposes a cooling device based on a thermal network model and a control method thereof, which can to a certain extent solve the technical problems such as the inability to monitor and predict the temperature of key parts inside the electric drive system, resulting in low cooling efficiency and accuracy.

[0005] In a first aspect of the present disclosure, a cooling device based on a thermal network model is provided, for cooling a load, the device comprising:

[0006] A coolant storage device, used for storing coolant;

[0007] a coolant valve connected to the load and a preset position in a driver of the load, for providing a corresponding amount of coolant to the preset position to cool the preset position;

[0008] A controller, connected between the coolant storage and the coolant valve, is used to:

[0009] A thermal network model is constructed based on the real-time operating parameters of the load and the driver, and the current amount of coolant required for the preset position is determined based on the thermal network model; and / or, the working condition of the load in a preset time period is predicted based on the real-time operating parameters to obtain a predicted working condition; and a predicted amount of coolant corresponding to the preset position is obtained based on the predicted working condition; wherein the real-time operating parameters include at least one of the following: the real-time speed of the load, the stator temperature of the load, the driver temperature of the driver, the driver current of the driver, or the driver voltage of the driver;

[0010] The amount of coolant provided by the coolant valve to the preset position is controlled based on the current amount and / or the predicted amount.

[0011] In a second aspect of the present disclosure, a cooling control method based on a thermal network model is provided, comprising:

[0012] Acquire real-time operating parameters of a load and a driver of the load; wherein the real-time operating parameters include at least one of the following: a real-time rotation speed of the load, a stator temperature of the load, a driver temperature of the driver, a driver current of the driver, or a driver voltage of the driver;

[0013] Constructing a thermal network model of the load based on the real-time operating parameters; determining the current amount of coolant required for the load and the preset position of the driver based on the thermal network model; and / or predicting the working condition of the load in a preset time period based on the real-time operating parameters to obtain a predicted working condition; and obtaining a corresponding predicted amount of coolant based on the predicted working condition;

[0014] The amount of coolant provided by the coolant valve to the preset position is controlled based on the current amount and / or the predicted amount.

[0015] From the above, it can be seen that the present disclosure provides a cooling and control method based on a thermal network model, which performs real-time temperature calculation by establishing a thermal network model of the load and the driver, and / or predicts the future operating conditions of the load through the temperature signal, speed signal of the load and the current signal and voltage signal of the driver, and reasonably distributes the amount of coolant for each component inside the load, thereby improving the accuracy and efficiency of cooling, and avoiding excessive cooling performance, thereby saving the use of coolant, reducing cooling costs, and providing an important guarantee for the stable and safe operation of the load. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a schematic diagram of a cooling device based on a thermal network model according to an embodiment of the present disclosure.

[0018] Figure 2A-2B Schematic diagram of a controller according to an embodiment of the present disclosure.

[0019] Figure 3It is a schematic flow chart of a cooling control method based on a thermal network model according to an embodiment of the present disclosure.

[0020] Figure 4 A schematic diagram of a node network according to an embodiment of the present disclosure.

[0021] Figure 5 Schematic diagram of the composition of the thermal resistance between two nodes according to an embodiment of the present disclosure.

[0022] Figure 6 Schematic diagram of internal heat transfer of a winding between two nodes according to an embodiment of the present disclosure. Implementation

[0023] In order to make the objectives, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0024] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should be understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the embodiments of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0025] With the promotion of the low-carbon green development concept, relatively more energy-saving and efficient new energy electric traction devices have become popular, and the performance requirements for electric traction devices have gradually increased. High-power density electric drive systems can significantly reduce the cost and weight of the entire vehicle, greatly improve the power system of new energy traction devices, and comprehensively improve the efficiency and safety of electric traction devices. There are permanent magnet motors inside high-power density electric drive systems. When the temperature is too high, it is easy to cause irreversible demagnetization of the permanent magnets, affecting the smooth and safe operation of new energy traction devices.

[0026] For conventional new energy traction devices, oil-cooled flat wire motors are occupying the main market position in electric drive systems. The cooling flow control of the cooling system is basically constant. For safety reasons, there is a certain margin on the basis of meeting the internal motor peak power operation heat dissipation, which can fully meet the internal cooling needs of the drive system. However, in the overall multi-scenario application of the traction device, the conventional cooling system cannot monitor and predict the temperature of key parts inside the drive system, cannot know the temperature change trend of key components, and cannot be fully combined with the operating conditions of the traction device, which easily causes excessive cooling system performance.

[0027] At present, the relevant technologies for intelligent cooling control of the electric drive system inside the new energy traction device include using different branches to cool the entire traction device in the form of series and parallel connection; and controlling the coolant according to the temperature signal and the coolant demand table of each component. In actual use, the electric drive system of the traction device is often cooled with the maximum coolant demand, which is likely to cause the overall performance of the cooling system to be low, and it is also unable to clearly reflect the temperature change trend of the key components inside the drive system. Therefore, how to improve the cooling performance and efficiency under any working conditions has become a technical problem that needs to be solved urgently.

[0028] In view of this, the embodiments of the present disclosure provide a cooling device based on a thermal network model and a control method thereof, which performs real-time temperature calculation by establishing a thermal network model of the load and the driver, and / or predicts the future operating conditions of the load through the temperature signal, speed signal of the load and the current signal and voltage signal of the driver, and reasonably distributes the amount of coolant used in each component inside the load, thereby improving the accuracy and efficiency of cooling, and avoiding excessive cooling performance, thereby saving the use of coolant, reducing cooling costs, and providing an important guarantee for the stable and safe operation of the load. It can not only respond to the temperature change trend of key components in the electric drive system, but also accurately cool each component according to the cooling requirements, improve the comprehensive performance of the cooling system, and realize efficient and balanced cooling of the motor of the new energy traction device under the full range of operating conditions under multiple scenarios.

[0029] See also Figure 1 , Figure 1 A schematic diagram of a cooling device based on a thermal network model according to an embodiment of the present disclosure is shown. Figure 1 In the embodiment, the cooling device 100 based on the thermal network model may include:

[0030] A coolant storage 6, used for storing coolant;

[0031] a coolant valve 3 connected to the load 2 and a preset position of the driver 1 of the load, and used to provide a corresponding amount of coolant to the preset position to cool the preset position;

[0032] The controller 4 is connected between the coolant storage 6 and the coolant valve 3 and is used for:

[0033] A thermal network model is constructed based on the real-time operating parameters of the load and the driver, and the current amount of coolant required for the preset position is determined based on the thermal network model; and / or, the working condition of the load in a preset time period is predicted based on the real-time operating parameters to obtain a predicted working condition; and a predicted amount of coolant corresponding to the preset position is obtained based on the predicted working condition; wherein the real-time operating parameters include at least one of the following: the real-time speed of the load, the stator temperature of the load, the driver temperature of the driver, the driver current of the driver, or the driver voltage of the driver;

[0034] And, based on the current usage and / or the predicted usage, the amount of coolant provided by the coolant valve to the preset position is controlled.

[0035] Among them, the cooling device 100 can be used to cool the load 2. The load 2 can be a motor, and the driver 1 can be a motor driver. The controller can construct a thermal network model based on the real-time operating parameters to determine the current amount of coolant currently required for the preset position, so as to accurately and in real time control the amount of coolant provided by the coolant valve to the preset position (the preset position can refer to the position that needs to be cooled, which is not limited here) based on the current amount. It is also possible to predict the future operating conditions of the load (such as acceleration or deceleration, etc.) based on the real-time operating parameters to predict the predicted amount of coolant required by the preset position in a preset time period in the future. In this way, the supply of coolant can be controlled in advance based on the predicted amount. Compared with providing coolant in real time according to the current amount, the cooling response speed can be accelerated, and the cooling efficiency and cooling effect can be further improved, thereby ensuring the reliable operation of the load. The coolant usage of the coolant valve can also be controlled based on both the predicted usage and the current usage; for example, at time t1, the predicted usage of the coolant in the time period t2-t3 is predicted to be Q1, and at time t2, the current usage Q2 at time t2 can be calculated, and the predicted usage Q1 and the current predicted usage Q2 can be compared. When the two are consistent (for example, when the difference between the two is within a preset range, it can be determined that the two are consistent), the predicted usage Q1 is used to control the coolant usage of the coolant valve, and when the two are inconsistent, the current usage Q2 is used to control the coolant usage of the coolant valve. At the same time, when the two are inconsistent, the current usage Q2 at time t2 can be used to update the prediction model used to calculate the predicted usage to improve the prediction accuracy of the prediction model.

[0036] In some embodiments, the cooling device 100 may further include:

[0037] a pump 5 , arranged at the output port of the coolant storage 6 , for delivering the coolant in the coolant storage 6 to the coolant valve 3 via the controller 4 ;

[0038] A rotation speed sensor (not shown), provided on the load, for detecting the real-time rotation speed of the load 2;

[0039] a stator temperature sensor 7, arranged at a stator position in the load 2, for detecting a stator temperature of the stator;

[0040] A driver temperature sensor 8, disposed on the driver 1, for detecting the driver temperature of the driver 1;

[0041] A driver current sensor 9, provided on the driver 1, for detecting the driver current of the driver 1;

[0042] The driver voltage sensor 10 is disposed on the driver 1 and is used to detect the driver voltage of the driver 1 .

[0043] The rotation speed sensor may include a resolver sensor disposed inside the load 2 , and used to detect a real-time rotation speed signal of the load 2 .

[0044] In some embodiments, the controller 4 includes:

[0045] The inlet terminal 21 is connected to the rotation speed sensor, the stator temperature sensor, the driver temperature sensor, the driver current sensor and the driver voltage sensor, and is used to obtain the real-time operating parameters;

[0046] A model unit 22, connected to the incoming line end, is used to construct a thermal network model based on the real-time operating parameters, and determine the current amount of coolant required for the preset position based on the thermal network model; and / or, a working condition prediction unit 23, connected to the model unit 22, is used to predict the working condition of the load in a preset time period based on the real-time operating parameters to obtain a predicted working condition; and obtain a predicted amount of coolant corresponding to the predicted working condition;

[0047] an output unit 24, connected to the model unit and / or the operating condition prediction unit, for outputting a control instruction of the coolant valve based on the current usage and / or the predicted usage, so as to control the amount of coolant provided by the coolant valve to the preset position;

[0048] The output terminal is connected to the output unit and is used to send the control instruction.

[0049] Specifically, see Figure 2A-2B , Figure 2A-2B A schematic diagram of a controller according to an embodiment of the present disclosure is shown. Figure 2A-2BIn the figure, the incoming line (sensor connection line) of the incoming line terminal 21 is respectively connected to the speed signal of the rotary transformer sensor inside the traction device, the temperature signal of the stator temperature sensor 7, the temperature signal of the temperature sensor 8 in the motor driver, the current signal of the current sensor 9 inside the drive controller, and the voltage signal of the voltage sensor 10 inside the drive controller. The lead-out line 12 of the flow control module 4 is connected to the cooling oil electronic oil valve 3, which controls the cooling oil electronic oil valve 3 to control the coolant flow of each part of the cooling motor. The cooling oil pump 5 on the cooling oil tank 6 is connected to the flow control module 4 with a connecting hose to transport coolant. The cooling oil pump 5 is on the cooling oil tank 6 and is connected to the flow control module 4 through a hose (through the oil circuit) to transport coolant to the cooling system.

[0050] During driving, the temperature information processing unit 22 in the flow control module 4 processes the real-time speed, voltage signal, current signal, temperature signal and other data of the motor driver 1 and the drive motor 2, obtains the temperature of the corresponding important key components, and calculates the amount of coolant used to cool the motor driver 1 and the drive motor 2 at this time based on the above data. At the same time, the working condition prediction module 23 predicts the subsequent working condition of the drive motor 2 in combination with the above data, and calculates the subsequent oil consumption required for the motor driver 1 and the drive motor 2. The flow control module 8 combines the two sets of data obtained by the previous processing and issues a command to the cooling oil electronic oil valve 3, and the cooling oil electronic oil valve 3 controls the amount of coolant input into the motor driver 1 and the drive motor 2.

[0051] See also Figure 3 , Figure 3 A schematic flow chart of a cooling control method based on a thermal network model according to an embodiment of the present disclosure is shown. Figure 3 In the present invention, the cooling control method 300 based on the thermal network model may further include the following steps.

[0052] In step S310, real-time operating parameters of the load and the driver of the load are obtained; wherein the real-time operating parameters include at least one of the following: the real-time rotational speed of the load, the stator temperature of the load, the driver temperature of the driver, the driver current of the driver, or the driver voltage of the driver.

[0053] In step S320, a thermal network model of the load is constructed based on the real-time operating parameters; a current amount of coolant required for the current load and the preset position of the driver is determined based on the thermal network model; and / or, the operating condition of the load in a preset time period is predicted based on the real-time operating parameters to obtain a predicted operating condition; and a corresponding predicted amount of coolant is obtained based on the predicted operating condition.

[0054] In some embodiments, constructing a thermal network model about the load based on the real-time operating parameters includes:

[0055] Dividing the simplified model of the load into nodes along the axial direction according to the structural components of the load to obtain a node network related to the load;

[0056] Determining node losses, conduction thermal resistance, and convection thermal resistance of the nodes in the node network based on the real-time operating parameters;

[0057] A thermal balance equation for the node network is constructed based on the node loss, the conduction thermal resistance and the convection thermal resistance to obtain the thermal network model.

[0058] The controller 4 establishes a motor thermal network model under different operating environments and conditions according to real-time operating parameters such as the real-time speed of the load, the stator temperature of the load, the driver temperature of the driver, the driver current of the driver or the driver voltage of the driver, and couples the electric assembly loss model inside the electric drive system. Specifically, the motor adopts a built-in V-type permanent magnet synchronous motor, and the steps of establishing the thermal network model of the motor may include:

[0059] Firstly, the motor model is simplified to obtain a simplified model, and nodes are divided along the axial direction on the simplified model;

[0060] Secondly, the iron loss of the motor stator and rotor, the copper loss of the stator winding, and the eddy current loss of the permanent magnet are calculated according to the finite element method or analytical method, and the losses of each part are distributed according to the equal volume distribution principle;

[0061] Secondly, the thermal conductivity of each structural component in the motor and the convection heat transfer coefficient between fluid-solid coupling are solved by analytical method or finite volume method, and then the conduction thermal resistance and convection thermal resistance are calculated;

[0062] Then, the thermal balance equation is solved to obtain the temperature of each node of the discrete network. When using the LPTN (Lumped-parameter Thermal Network) method to calculate the motor temperature field, the following assumptions are made:

[0063] A1: In the radial direction, the temperature distribution of the motor is symmetrical;

[0064] A2: The skin effect of the winding is negligible;

[0065] A3: The mutual thermal conductivity between the two nodes is equal and has nothing to do with the temperature rise;

[0066] A4: The radiation heat transfer process of the motor is negligible;

[0067] Based on the above assumptions, the center of each area's geometric structure is used as a node, and each node is connected by thermal resistance. The motor structure network formed can solve the temperature field of the motor:

[0068] (1)

[0069] In formula (1), G is The n×1 thermal conductivity matrix; T is the n×1 temperature column matrix; W is the n×1 temperature column matrix.

[0070] The above equations can be solved to get the temperature value of each node. Among them, the actual heat inside the motor will not only be along the axial direction, but will be carried out simultaneously in the axial and radial directions. At the same time, the division of nodes needs to be considered comprehensively. Whether the conduction thermal resistance and convection thermal resistance inside the motor can be accurately calculated is directly related to the accuracy of the motor temperature calculation. The thermal resistance value is affected by many factors such as temperature, flow rate, area, and material. For example, the thermal conductivity of the material itself is affected by factors such as material properties and component manufacturing; the convection heat transfer coefficient between the cooling fluid and the solid material is affected by the material properties of the fluid itself. The calculation formula is different in different temperature ranges, and it is affected by the state of the moving airflow inside the motor, and can only be measured under specific conditions. Therefore, the thermal resistance in the thermal network model is usually calculated by an equivalent formula.

[0071] In some embodiments, determining the conduction thermal resistance and the convection thermal resistance of the node in the node network based on the real-time operating parameters includes:

[0072] determining the conduction thermal resistance between the node and the adjacent node based on the distance, contact area and thermal conductivity between the node and the adjacent node;

[0073] The convection thermal resistance between the node and the adjacent node is determined based on the distance between the node and the adjacent node, the convection area, and the heat dissipation coefficient.

[0074] There are three main ways of heat transfer inside the motor: heat conduction, heat transfer, and heat radiation. When analyzing the temperature field of the motor, the temperature generated by heat radiation only accounts for a small part, and usually only two heat transfer methods, heat conduction and heat convection, are considered. Therefore, the present invention directly divides the thermal resistance inside the motor into two categories: conduction thermal resistance and convection thermal resistance. Convection thermal resistance The calculation formulas of the two thermal resistances are:

[0075] (2)

[0076] (3)

[0077] Where:

[0078] ----The distance between two nodes;

[0079] ----Contact surface area;

[0080] ----Convection area;

[0081] ----Thermal conductivity;

[0082] ----Heat dissipation coefficient.

[0083] Based on this, the prototype is divided into different areas, and nodes are set up in the center of each area. The division of areas and the establishment of nodes should fully consider factors such as the structure and material of the motor.

[0084] In some embodiments, dividing the simplified model of the load along the axial direction according to the structural components of the load to obtain a node network related to the load includes:

[0085] The casing is axially divided into five equal parts: the casing node, stator yoke node, lower winding node, inter-winding insulation node, upper winding node, stator tooth node; air gap node; upper permanent magnet node, permanent magnet node, rotor node, shaft node, bearing node, front and rear end cover nodes and front and rear machine cavity nodes.

[0086] Specifically, see Figure 4 , Figure 4 A schematic diagram of a node network according to an embodiment of the present disclosure is shown. Figure 4 Among them, 1-5 are the casing nodes, which divide the casing axially into five equal parts, 6-8 are the stator yoke nodes, 9-13 are the lower winding nodes, 14-16 are the winding interlayer insulation nodes, 17-21 are the upper winding nodes, 22-24 are the stator tooth nodes; 25-27 are the air gap nodes; 28-30 are the upper nodes of the permanent magnet, 31-33 are the permanent magnet nodes, 34-36 are the rotor nodes, 37-41 are the shaft nodes, 42-43 are the bearing nodes, 44-45 are the front and rear end cover nodes, 46-47 are the front and rear machine cavity nodes, and 48 is the reference node.

[0087] After the node division is completed, the calculation of thermal resistance in the thermal network model is explained by taking each casing and stator winding as an example.

[0088] The motor housing nodes are nodes 1-5, of which nodes 1 and 5 are the same type, and nodes 2, 3, and 4 are the same type. The heat dissipation of the motor housing is divided into two heat dissipation paths. One is the conduction from the housing node to the stator core node through 1 / 2 of the housing thickness, and the other is through 1 / 2 of the housing thickness to the housing surface, and then the heat on the housing surface is taken away by natural convection. The conduction thermal resistance of the housing from the upward transfer to the housing surface and the conduction thermal resistance from the downward transfer to the stator yoke are both cylindrical transfer models. Taking nodes 1 and 2 as examples, the thermal resistance is analyzed.

[0089] Take node 1 as an example:

[0090] (1) The conduction thermal resistance between node 1 and the housing node 2 is:

[0091] (4)

[0092] In formula (4): is the axial length of the casing; is the axial length of the stator and rotor; is the thermal conductivity of the casing; is the heat conduction area between nodes 1 and 2; is the outer diameter of the casing; is the stator outer diameter.

[0093] (2) The conduction thermal resistance between node 1 and the front cover node 44 is:

[0094] (5)

[0095] In formula (5): is the axial heat conduction area between nodes 1 and 44, equal to ; is the end cap thickness.

[0096] (3) The convection heat dissipation resistance between node 1 and cavity node 46 is:

[0097] (6)

[0098] In formula (6): is the convection heat dissipation area of ​​node 1 and node 46; is the convection heat transfer coefficient between the motor housing and the left side cavity (node ​​46).

[0099] (4) The convection heat dissipation resistance between node 1 and air node 48 (reference node) is:

[0100] (7)

[0101] In formula (7): is the convection heat dissipation area between node 1 and air node 48; is the convective heat transfer coefficient between casing node 1 and the air above.

[0102] Thermal resistance calculation taking node 6 (stator yoke) as an example:

[0103] There is heat exchange between the node 6 and the housing node 2 , the stator yoke node 7 , the lower winding node 10 , the stator tooth node 22 and the machine cavity node 46 .

[0104] (1) The conduction thermal resistance between node 6 and housing node 2 is:

[0105] (8)

[0106] In formula (8): is the stator yoke height, is the thermal conductivity of the stator yoke, is the radial thermal conductivity of silicon steel sheet.

[0107] (2) The conduction thermal resistance between node 6 and stator yoke node 7 is:

[0108] (9)

[0109] In formula (9): is the heat conduction area between nodes 6 and 7, is the thermal conductivity of the stator yoke.

[0110] (3) Thermal conduction resistance between node 6 and lower winding node 10

[0111] There are many materials in the heat path between the node 6 and the lower winding node 10, so its thermal resistance is also composed of many branches. For the stator winding: the main heat transfer paths of the stator winding are: from the insulation in the stator slot to the stator yoke; from the insulation in the stator slot to the stator teeth; in the axial direction inside the stator winding; from the winding to the winding end, such as Figure 5 and Figure 6 As shown, Figure 5 FIG. 4 shows a schematic diagram of the composition of the thermal resistance between two nodes according to an embodiment of the present disclosure, Figure 6 A schematic diagram of internal heat transfer in a winding between two nodes according to an embodiment of the present disclosure is shown. Figure 5 and Figure 6 The calculation methods of thermal resistance of each branch are basically the same, so the thermal resistance of the branch is used here. Take the calculation as an example.

[0112] (10)

[0113] In formula (10): is the heat conduction area of ​​the core between nodes 6 and 10, is the number of stator slots, is the winding width, is the main insulation thickness, is the thermal resistance of the lower winding when transferring heat through the left main insulation ③, is the thermal resistance of the lower winding when heat is transferred through the upper main insulation ①, is the thermal resistance of the lower winding itself, It is the thermal resistance of the lower winding when heat is transferred through the right main insulation ③.

[0114] (4) Thermal conduction resistance between node 6 and stator tooth node 22

[0115] The motor has a parallel slot structure and the stator teeth of the motor have an arc structure. The thermal resistance between the stator yoke node 6 and the stator tooth node 22 is calculated as follows:

[0116] (11)

[0117] In formula (11): is the inner diameter of the stator, is the stator slot height, It is the central angle occupied by a single stator tooth.

[0118] (5) Convective heat dissipation resistance between node 6 and cavity node 46

[0119] (12)

[0120] In formula (12): is the convection heat dissipation coefficient of the silicon steel sheet surface, It is the convection heat dissipation area of ​​the node between the silicon steel sheet and the machine cavity.

[0121] Similar to the case node and stator node, the conduction thermal resistance and convection thermal resistance between other nodes can also be calculated. The conduction thermal resistance and convection thermal resistance of each node and the node loss are brought into the heat balance equation for solution. Among them, the heat balance equation is based on the principle of heat balance, which means that under the stable state of heat flow, the sum of the heat generated by a node itself and the heat flowing into this node is equal to the heat flowing out of this node. Therefore, the general form of the heat balance equation between each node in the load (such as a motor) is:

[0122] (13)

[0123] In formula (13), is the temperature rise of node i, for and The mutual thermal conductance between nodes is equal to the mutual thermal conductance between nodes j and i , whose value is equal to the reciprocal of the thermal resistance between the i-node and the j-node. It is the self-thermal conductance of node i, and its value is equal to the sum of the reciprocals of the thermal resistances of all branches connected to node i.

[0124] The matrix form can be expressed as:

[0125] (14)

[0126] In formula (14): is the thermal conductivity matrix, is the node temperature matrix, is the node heat source loss matrix. According to the established thermal network model, the calculated thermal resistance between each node, the known node loss and the node temperature (i.e., the reference node temperature, as the reference temperature) are brought into the above heat balance equation to solve the temperature of each node in the motor.

[0127] In some embodiments, determining the node loss of the node in the node network based on the real-time operating parameter includes:

[0128] Calculating the stator iron loss, rotor iron loss, stator winding copper loss, and permanent magnet eddy current loss of the load based on the real-time operating parameters;

[0129] For the structural components corresponding to the stator iron loss, the rotor iron loss, the stator winding copper loss, and the permanent magnet eddy current loss, determine the component loss corresponding to each structural component according to the volume size of the area in the structural component corresponding to the node;

[0130] The component loss is evenly distributed to the nodes corresponding to the structural components to obtain the node loss.

[0131] In some embodiments, for the structural components corresponding to the stator iron loss, the rotor iron loss, the stator winding copper loss, and the permanent magnet eddy current loss, the component loss corresponding to each structural component is determined according to the volume size of the area in the structural component corresponding to the node; the component loss is evenly distributed to the node corresponding to the structural component to obtain the node loss, including:

[0132] The first ratio of the stator iron loss is determined as the first loss of the stator yoke, and the second ratio of the stator iron loss is determined as the second loss of the stator tooth; wherein the ratio of the first ratio to the second ratio is the volume ratio of the stator yoke to the stator tooth; the first loss is divided equally based on the number of nodes of the stator yoke to obtain the stator yoke node loss of the stator yoke node; the second loss is divided equally based on the number of nodes of the stator tooth to obtain the stator tooth node loss of the stator tooth node.

[0133] Specifically, for the stator iron loss, the stator iron loss of the motor can be calculated by the existing electromagnetic calculation module, or it can be manually input. After determining the stator iron loss, the stator iron loss is allocated, and the stator iron loss is allocated to the stator yoke and the stator teeth in a ratio of 3-7. And the allocated iron loss is divided into three equal parts to the stator yoke nodes 6-8 and the stator tooth nodes 22-24. For example, the stator iron loss is x, the stator yoke is 30%*x and the stator tooth is 70%*x; the stator yoke node is 10%*x, and the stator tooth node is 70%*x / 3.

[0134] In some embodiments, for the structural component corresponding to the winding copper loss, determining the node loss corresponding to the node according to the volume size of the area in the structural component corresponding to the node includes:

[0135] The third proportion of the winding copper loss is determined as the third loss of the lower winding, and the fourth proportion of the winding copper loss is determined as the fourth loss of the upper winding; wherein the ratio of the third proportion to the fourth proportion is the volume ratio of the lower winding to the upper winding; the third loss is equally divided based on the number of nodes of the lower winding to obtain the node loss of the lower winding of the lower winding; the fourth loss is equally divided based on the number of nodes of the upper winding to obtain the node loss of the upper winding of the upper winding.

[0136] Specifically, for the winding copper loss, the motor winding copper loss can also be calculated by the existing electromagnetic calculation module, or manually input. After the motor winding copper loss is determined, the motor winding copper loss is allocated, and the winding copper loss is allocated according to the volumes of the winding end and the straight segment, and the allocated end copper loss and straight segment copper loss are evenly distributed to nodes 9-13 and 17-21 respectively.

[0137] Similarly, the stator iron loss and permanent magnet eddy current loss can also be obtained by the existing calculation module, or manually input. After determining the stator iron loss and permanent magnet eddy current loss of the motor, when distributing the stator iron loss and permanent magnet eddy current loss, the stator iron loss and permanent magnet eddy current loss can also be distributed to each component according to the volume of the component in the stator and the volume of the component in the permanent magnet, and then the nodes corresponding to the components are further distributed (for example, evenly distributed) to obtain the node loss of each associated node of the stator iron loss and permanent magnet eddy current loss.

[0138] In some embodiments, determining the current amount of coolant required for the current load and the preset position of the driver based on the thermal network model includes:

[0139] Bringing the reference temperature of the node, the node loss, and the conduction thermal resistance and the convection thermal resistance between the nodes into the thermal balance equation for iteration to obtain the current temperature of the node;

[0140] A current usage of the coolant at the preset location is determined based on the current temperature.

[0141] In step S330 , the amount of coolant provided by the coolant valve to the preset position is controlled based on the current amount and / or the predicted amount.

[0142] Specifically, the amount of coolant provided by the coolant valve to the preset position can be accurately and in real time controlled based on the current amount. The future working conditions of the load (such as acceleration or deceleration, etc.) can also be predicted based on real-time operating parameters to predict the predicted amount of coolant required by the preset position in the preset time period in the future. In this way, the supply of coolant can be controlled in advance based on the predicted amount. Compared with providing coolant in real time according to the current amount, the cooling response speed can be accelerated, and the cooling efficiency and cooling effect can be further improved, thereby ensuring the reliable operation of the load. The coolant amount of the coolant valve can also be controlled based on both the predicted amount and the current amount; for example, at time t1, the predicted amount of coolant in the time period t2-t3 is predicted to be Q1, and at time t2, the current amount Q2 at time t2 can be calculated, and the predicted amount Q1 and the current predicted amount Q2 can be compared. When the two are consistent (for example, when the difference between the two is within a preset range, it can be determined that the two are consistent), the predicted amount Q1 is used to control the coolant amount of the coolant valve, and when the two are inconsistent, the current amount Q2 is used to control the coolant amount of the coolant valve. At the same time, when the two are inconsistent, the current usage Q2 at time t2 can be used to update the prediction model used to calculate the predicted usage, so as to improve the prediction accuracy of the prediction model.

[0143] It should be understood by those skilled in the art that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples; based on the concept of the present disclosure, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of different aspects of the embodiments of the present disclosure as described above, which are not provided in detail for the sake of simplicity.

[0144] In addition, to simplify the description and discussion, and in order not to obscure the embodiments of the present disclosure, known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided figures. In addition, devices may be shown in the form of block diagrams to avoid obscuring the embodiments of the present disclosure, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure are to be implemented (i.e., these details should be fully within the scope of understanding of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present disclosure, it is apparent to those skilled in the art that the embodiments of the present disclosure may be implemented without these specific details or with variations in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0145] Although the present disclosure has been described in conjunction with specific embodiments of the present disclosure, many alternatives, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the discussed embodiments.

[0146] The embodiments of the present disclosure are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A cooling device based on a thermal network model, characterized in that: For cooling a load, the device comprises: A coolant storage device, used for storing coolant; a coolant valve connected to the load and a preset position in a driver of the load, for providing a corresponding amount of coolant to the preset position to cool the preset position; A controller, connected between the coolant storage and the coolant valve, is used to: A thermal network model is constructed based on the real-time operating parameters of the load and the driver, and the current amount of coolant required for the preset position is determined based on the thermal network model; and / or, the working condition of the load in a preset time period is predicted based on the real-time operating parameters to obtain a predicted working condition; and a predicted amount of coolant corresponding to the preset position is obtained based on the predicted working condition; wherein the real-time operating parameters include at least one of the following: the real-time speed of the load, the stator temperature of the load, the driver temperature of the driver, the driver current of the driver, or the driver voltage of the driver; and, controlling the amount of coolant provided by the coolant valve to the preset position based on the current amount and / or the predicted amount; It also includes: a pump, disposed at an output port of the coolant storage device, for delivering the coolant in the coolant storage device to the coolant valve via the controller; A rotation speed sensor, arranged on the load, for detecting the real-time rotation speed of the load; a stator temperature sensor, disposed at a stator position in the load, for detecting a stator temperature of the stator; A driver temperature sensor, disposed on the driver, for detecting a driver temperature of the driver; A driver current sensor, disposed on the driver, for detecting a driver current of the driver; a driver voltage sensor, disposed on the driver, for detecting a driver voltage of the driver; Wherein, the controller comprises: An inlet terminal connected to the rotation speed sensor, the stator temperature sensor, the driver temperature sensor, the driver current sensor and the driver voltage sensor, for acquiring the real-time operating parameters; A model unit connected to the inlet terminal, used to construct a thermal network model based on the real-time operating parameters, and determine the current amount of coolant required for the preset position based on the thermal network model; and / or, a working condition prediction unit connected to the model unit, used to predict the working condition of the load in a preset time period based on the real-time operating parameters to obtain a predicted working condition; and obtain a predicted amount of coolant corresponding to the predicted working condition; an output unit connected to the model unit and / or the operating condition prediction unit, and configured to output a control instruction of the coolant valve based on the current usage and / or the predicted usage, so as to control the amount of coolant provided by the coolant valve to the preset position; The output terminal is connected to the output unit and is used to send the control instruction.

2. A cooling control method based on a thermal network model, characterized in that: include: Acquire real-time operating parameters of a load and a driver of the load; wherein the real-time operating parameters include at least one of the following: a real-time rotation speed of the load, a stator temperature of the load, a driver temperature of the driver, a driver current of the driver, or a driver voltage of the driver; Constructing a thermal network model of the load based on the real-time operating parameters; determining the current amount of coolant required for the load and the preset position of the driver based on the thermal network model; and / or predicting the working condition of the load in a preset time period based on the real-time operating parameters to obtain a predicted working condition; and obtaining a corresponding predicted amount of coolant based on the predicted working condition; The amount of coolant provided by the coolant valve to the preset position is controlled based on the current amount and / or the predicted amount.

3. The method according to claim 2, characterized in that The step of constructing a thermal network model for the load based on the real-time operating parameters includes: Dividing the simplified model of the load into nodes along the axial direction according to the structural components of the load to obtain a node network related to the load; Determining node losses, conduction thermal resistance, and convection thermal resistance of the nodes in the node network based on the real-time operating parameters; A thermal balance equation for the node network is constructed based on the node loss, the conduction thermal resistance and the convection thermal resistance to obtain the thermal network model.

4. The method according to claim 3, characterized in that The determining the node loss of the node in the node network based on the real-time operating parameter comprises: Calculating the stator iron loss, rotor iron loss, stator winding copper loss, and permanent magnet eddy current loss of the load based on the real-time operating parameters; And for the structural components corresponding to the stator iron loss, the rotor iron loss, the stator winding copper loss, and the permanent magnet eddy current loss, the component loss corresponding to each structural component is determined according to the volume size of the area in the structural component corresponding to the node; The component loss is evenly distributed to the nodes corresponding to the structural components to obtain the node loss.

5. The method according to claim 4, characterized in that The determining the conduction thermal resistance and the convection thermal resistance of the node in the node network based on the real-time operating parameters comprises: determining the conduction thermal resistance between the node and the adjacent node based on the distance, contact area and thermal conductivity between the node and the adjacent node; The convection thermal resistance between the node and the adjacent node is determined based on the distance between the node and the adjacent node, the convection area, and the heat dissipation coefficient.

6. The method according to claim 5, characterized in that The heat balance equation of the node network includes: -G(1,i)*T(1)··+G(i,i)*T(i)··-G(j,i)*T(j)=P(i), Where T(i) is the temperature rise of node i, G(j, i) is the mutual thermal conductance between nodes i and j, which is the reciprocal of the thermal resistance between nodes i and j; G(i, i) is the self-thermal conductance of node i, which is the sum of the reciprocals of the thermal resistances on the branches of all nodes connected to node i; P(i) is the heat source loss of node i.

7. The method according to claim 6, characterized in that Determining a current amount of coolant required for the current load and the preset position of the driver based on the thermal network model includes: Bringing the reference temperature of the node, the node loss, and the conduction thermal resistance and the convection thermal resistance between the nodes into the thermal balance equation for iteration to obtain the current temperature of the node; A current usage of the coolant at the preset location is determined based on the current temperature.

8. The method according to claim 7, characterized in that The simplified model of the load is divided into nodes along the axial direction according to the structural components of the load to obtain a node network about the load, including: The casing is divided into five equal parts in the axial direction, namely, the casing node, the stator yoke node, the lower winding node, the winding interlayer insulation node, the upper winding node, the stator tooth node, the air gap node, the permanent magnet upper node, the permanent magnet node, the rotor node, the shaft node, the bearing node, the front and rear end cover nodes and the front and rear machine cavity nodes; Determine the first ratio of the stator iron loss as the first loss of the stator yoke, and determine the second ratio of the stator iron loss as the second loss of the stator tooth; wherein the ratio of the first ratio to the second ratio is the volume ratio of the stator yoke to the stator tooth; divide the first loss based on the number of nodes of the stator yoke to obtain the stator yoke node loss of the stator yoke node; divide the second loss based on the number of nodes of the stator tooth to obtain the stator tooth node loss of the stator tooth node; The third proportion of the winding copper loss is determined as the third loss of the lower winding, and the fourth proportion of the winding copper loss is determined as the fourth loss of the upper winding; wherein the ratio of the third proportion to the fourth proportion is the volume ratio of the lower winding to the upper winding; the third loss is equally divided based on the number of nodes of the lower winding to obtain the node loss of the lower winding of the lower winding; the fourth loss is equally divided based on the number of nodes of the upper winding to obtain the node loss of the upper winding of the upper winding.

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