Liquid cooling thermal management system and control method for a fast charging gun

Abstract

This invention relates to the field of electric vehicle charging equipment technology, and discloses a liquid-cooled thermal management system and control method for a fast charging gun. The system includes a temperature acquisition module, a heat load calculation module, a demand flow calculation module, a flow allocation optimization module, a valve control execution module, and a cyclic scheduling module. Based on a parallel multi-segment independent branch liquid-cooled circuit, the system independently calculates the real-time heat generation power and coolant demand flow for each segment. A quadratic programming solution is performed with the goal of minimizing the total output power of the liquid-cooled pump, outputting the optimal opening command set for the electromagnetic proportional valves of each parallel branch, thereby achieving independent allocation of coolant flow for each segment.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging equipment technology, specifically to a liquid-cooled thermal management system and control method for a fast charging gun. Background Technology

[0002] When a fast charging gun operates under high current conditions, the heat flux density in the gun head connector section is high due to the concentration of contact resistance. The heat dissipation of the flexible cable section in the middle is limited by natural convection due to bending and winding. The heat dissipation of the charging pile end section is relatively good due to its large exposed area. The heating characteristics of each physical section are significantly different.

[0003] Existing liquid-cooled thermal management systems generally use a single coolant series loop, with the coolant flowing through all sections sequentially. The overall circulation flow is driven by a unified liquid-cooled pump, and the control unit adjusts the pump speed only based on the highest temperature value of a few temperature acquisition points.

[0004] In a series configuration, the coolant temperature continues to rise after flowing through the upstream high-heat section, and its heat-carrying capacity decreases when it reaches the downstream section, creating a risk of localized hotspot accumulation. Meanwhile, a single flow control strategy cannot target the differentiated heat dissipation needs of each section. The high flow rate maintained to meet the cooling requirements of the highest heat load section results in excess coolant flow in the low heat load section, causing the liquid-cooled pump power consumption to remain high and reducing the overall energy efficiency of the fast-charging system. Summary of the Invention

[0005] This invention provides a liquid-cooled thermal management system and control method for a fast charging gun, solving the technical problems of uneven temperature distribution in different sections of fast charging cables and low cooling efficiency of liquid cooling systems in related technologies.

[0006] This invention discloses a liquid cooling and thermal management control method for fast charging guns, comprising the following steps:

[0007] The real-time temperature data of multiple temperature sensors distributed along the charging gun cable is acquired, and the cable is divided into the gun head connector section, the intermediate flexible cable section and the pile end connection section, and a real-time temperature vector of each section is generated.

[0008] The real-time charging current value is obtained, and combined with the pre-stored resistance characteristic parameters of each section, the real-time heating power of each section is calculated according to the Joule heating calculation model to generate a heat load dataset for each section.

[0009] Based on the heat load dataset and real-time temperature vector of each section, the minimum coolant volume flow rate required to maintain the temperature at its respective target temperature threshold in each section is calculated by substituting the heat balance equation of each section into the heat balance equation of each section, and the coolant demand flow rate value of each section is generated.

[0010] With the objective function of minimizing the total output power consumption of the liquid cooling pump and the constraint that the actual flow rate of each section is not lower than the corresponding coolant demand flow rate, a quadratic programming algorithm is executed to solve for the optimal opening command set of the electromagnetic proportional valves in each parallel branch.

[0011] The optimal opening command set is distributed to the electromagnetic proportional valves corresponding to each parallel branch of the liquid cooling circuit, and the coolant flow rate of each independent branch is adjusted respectively.

[0012] Furthermore, the real-time temperature vector for each section is a one-dimensional numerical sequence composed of the collected values ​​of all temperature sensors within that section, arranged in the physical order of the sensors along the cable direction.

[0013] Furthermore, the real-time heating power of each segment is calculated according to the Joule heating calculation model, including: reading the equivalent resistance value of each segment, which is the equivalent total resistance after combining the DC resistance of the conductor and the contact resistance in the segment; the real-time heating power of each segment is equal to the product of the square of the real-time charging current value and the equivalent resistance value of the corresponding segment.

[0014] Furthermore, the equivalent resistance value of each section is temperature-corrected based on the arithmetic mean of all sensor readings in the real-time temperature vector of each section. The correction method is to multiply the original equivalent resistance value by a temperature correction factor. The temperature correction factor is equal to... ,in The temperature coefficient of resistance of a conductor material. This is the difference between the arithmetic mean temperature of this section and the reference temperature. The corrected equivalent resistance value is substituted into the Joule heating calculation model instead of the original equivalent resistance value.

[0015] Furthermore, calculating the minimum coolant volumetric flow rate required to maintain the temperature at its respective target temperature threshold for each section includes: obtaining the preset target temperature threshold, specific heat capacity, density, and inlet temperature of the coolant for each section; and establishing a steady-state heat balance equation for each section. The required coolant volumetric flow rate for each section is... ,in Volumetric flow rate, This represents the real-time heating power of this section. For coolant density, The specific heat capacity of the coolant. This is the target temperature threshold for this section. This refers to the coolant inlet temperature. The target temperature threshold for each section is the upper limit of the allowable steady-state operating temperature for that section, and each section has a different value set independently.

[0016] Furthermore, when the difference between the maximum value in the real-time temperature vector of a certain segment and the target temperature threshold of that segment is less than a preset margin threshold, the demand flow value of that segment is multiplied by a margin coefficient greater than 1 to obtain the corrected demand flow value; when the difference is not less than the margin threshold, the demand flow value of that segment is not corrected.

[0017] Furthermore, the quadratic programming algorithm involves defining the optimization variable as the opening value of the electromagnetic proportional valve in each parallel branch. The actual coolant volumetric flow rate of each branch is equal to... ,in This is the valve opening value for this branch. This represents the maximum flow rate when the valves in this branch are fully open. The total flow rate of the liquid cooling pump is the sum of the actual flow rates of each branch. The objective function is a quadratic polynomial of the total output power of the liquid cooling pump in terms of the total flow rate. ,in The fitting coefficients are pre-calibrated using liquid-cooled pump performance test data. Constraints include that the actual flow rate of each branch is not less than the coolant demand flow rate of the corresponding section, and that the valve opening value of each branch is within the range of zero to one. Substituting the expressions for the actual flow rates of each branch into the objective function and constraints, a convex quadratic programming problem with linear inequality constraints is solved to obtain the optimal valve opening value.

[0018] Furthermore, before executing the quadratic programming algorithm, the process includes: obtaining the predicted charging current value for the next control cycle sent by the charging controller; calculating the predicted heat generation power and predicted coolant demand flow rate for each segment based on the predicted charging current value; and using the larger of the current coolant demand flow rate for each segment and the predicted coolant demand flow rate as the lower limit of the flow rate in the constraint conditions.

[0019] Furthermore, the system iteratively executes the following steps in a preset control cycle: acquiring the real-time temperature vector of each segment, calculating the real-time heat generation power of each segment, calculating the coolant flow demand value of each segment, solving for the optimal opening instruction set, and distributing the optimal opening instruction set. After each control cycle is completed, the real-time temperature vector of each segment, the heat load dataset of each segment, the coolant flow demand value of each segment, and the optimal opening instruction set of the current cycle are stored in non-volatile memory according to timestamps, forming the charging session thermal management log data.

[0020] This invention discloses a liquid cooling and heating management system for fast charging guns, used to execute the aforementioned liquid cooling and heating management control method for fast charging guns. The system includes:

[0021] The temperature acquisition module is used to acquire real-time temperature data from multiple temperature sensors distributed along the charging gun cable, divide the cable into the gun head connector section, the intermediate flexible cable section and the pile end connection section, and generate real-time temperature vectors for each section.

[0022] The heat load calculation module is used to obtain the real-time charging current value, combine it with the pre-stored resistance characteristic parameters of each section, calculate the real-time heating power of each section according to the Joule heating calculation model, and generate heat load datasets for each section.

[0023] The demand flow calculation module is used to calculate the minimum coolant volume flow rate required for each section to maintain the temperature at its respective target temperature threshold based on the heat load dataset and real-time temperature vector of each section, and to generate the coolant demand flow rate value of each section.

[0024] The flow distribution optimization module is used to minimize the total output power consumption of the liquid cooling pump as the objective function and with the constraint that the actual flow rate of each section is not lower than the corresponding coolant demand flow rate, and to execute a quadratic programming algorithm to solve for the optimal opening instruction set of the electromagnetic proportional valves of each parallel branch.

[0025] The valve control execution module is used to distribute the optimal opening command set to the electromagnetic proportional valves corresponding to each parallel branch of the liquid cooling circuit, so as to adjust the coolant flow rate of each independent branch.

[0026] The cyclic scheduling module is used to trigger the temperature acquisition module, heat load calculation module, demand flow calculation module, flow allocation optimization module and valve control execution module to execute in sequence according to a preset control cycle, so as to realize dynamic flow redistribution and adjustment throughout the fast charging process.

[0027] The beneficial effects of this invention are as follows:

[0028] This invention reconstructs the liquid cooling circuit from a series structure to a parallel multi-segment independent branch structure. Each segment's coolant flows independently through its corresponding segment after being diverted from a common inlet manifold. This eliminates the cumulative effect of the coolant's heat-carrying capacity gradually decreasing after flowing through the upstream high-heat segment in a series circuit, thus solving the technical problem of local hotspot accumulation in the downstream segment of a series circuit. It achieves the technical effect of consistent coolant inlet temperature across all segments without interference. Based on the parallel circuit structure, by independently calculating the real-time heat load and coolant flow demand for each segment, and performing a quadratic programming solution with the goal of minimizing the total output power of the liquid cooling pump and the temperature constraints of each segment as the constraint condition, this invention solves the technical problem of mismatch between coolant supply and actual heat dissipation demand in each segment and high liquid cooling pump power consumption under a single flow control strategy. It achieves the technical effect of reducing the operating power consumption of the liquid cooling pump while meeting the thermal safety requirements of each segment. Attached Figure Description

[0029] Figure 1 This is a flowchart of the liquid cooling and heating management control method for fast charging guns provided in an embodiment of the present invention. Detailed Implementation

[0030] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, some features described in the examples may be combined in other examples.

[0031] At least one embodiment of the present invention discloses a liquid cooling and thermal management control method for fast charging guns, see [link to relevant documentation]. Figure 1 This includes the following steps:

[0032] Step S1: Obtain the real-time temperature vector for each section.

[0033] The system acquires real-time temperature data from multiple temperature sensors distributed along the entire length of the charging gun cable. Based on the physical installation location of each temperature sensor, the cable is divided into three sections: the gun head connector section, the intermediate flexible cable section, and the charging pile connection section. The temperature sensor data collected for each section is extracted to generate a real-time temperature vector for each section.

[0034] It should be noted that the real-time temperature vector for each of the above sections is a one-dimensional numerical sequence composed of the collected values ​​from all temperature sensors within that section, arranged in the physical order of the sensors along the cable direction. For example, the gun head connector section is arranged with... If there are multiple temperature sensors, then the real-time temperature vector of the nozzle connector section is: ,in Indicates the gun head connector section number The temperature value of each temperature sensor at the current sampling time. Temperature vector of the intermediate flexible cable section and the pile end connection section. and Generate in the same way.

[0035] Step S2: Calculate the real-time heating power of each section.

[0036] Get the real-time charging current value of the current fast charging session. The system reads the pre-stored resistance characteristics of cables and connectors in each section, calculates the real-time heating power of each section according to the Joule heating calculation model, and generates a heat load dataset for each section.

[0037] Step S2 may specifically include:

[0038] Step S201: Obtain the real-time charging current value from the charging controller communication interface. .

[0039] Step S202: Read the equivalent resistance value of each section from the pre-stored parameter table, where the equivalent resistance of the gun head connector section is... The equivalent resistance of the intermediate flexible cable section is The equivalent resistance of the pile end connection section is .

[0040] Step S203: Calculate the real-time heating power of each section:

[0041] ;

[0042] ;

[0043] ;

[0044] in, , , These are the real-time heat generation power of the gun head connector section, the intermediate flexible cable section, and the pile end connection section, respectively. , , The heat load datasets for each section are constructed.

[0045] It should be noted that the equivalent resistance values ​​for each of the above sections are the total equivalent resistance after comprehensively considering the DC resistance of the conductor and the contact resistance within that section. For the gun head connector section, This includes the contact resistance component between the terminal and the contact finger, as well as the conductor body resistance component of the gun head connector section. For the intermediate flexible cable section and the terminal connection section... and It is mainly composed of the resistance of the conductor body in the corresponding section.

[0046] In this embodiment, to obtain a more accurate estimate of heat generation power during cable temperature changes, the equivalent resistance value of each segment can be temperature-corrected based on the representative temperature in the real-time temperature vector of each segment. Specifically, the equivalent resistance of each segment is corrected in the following manner:

[0047] ;

[0048] ;

[0049] ;

[0050] in, , , These are the corrected equivalent resistance values ​​for each section; The temperature coefficient of resistance of a conductor material; , , These are the arithmetic mean values ​​of all sensor data collected in the real-time temperature vector of each section; This is the reference temperature corresponding to the resistance characteristic parameters. The corrected equivalent resistance value is substituted into the Joule heating calculation model instead of the original equivalent resistance value to recalculate the real-time heating power of each section.

[0051] Step S3: Calculate the required coolant flow rate for each section.

[0052] Based on the heat load dataset and real-time temperature vector of each section, the minimum coolant volume flow rate required to maintain the temperature at its target temperature threshold under the current heat output power is calculated by substituting the heat balance equation of each section into the heat balance equation of each section, and the coolant demand flow rate value of each section is generated.

[0053] Step S3 may specifically include:

[0054] Step S301: Obtain the preset target temperature threshold for each segment. , , and the specific heat capacity of the coolant ,density and coolant inlet temperature .

[0055] Step S302: Establish steady-state thermal balance equations for each section. Taking the nozzle connector section as an example, under steady-state conditions, the heat generated in the nozzle connector section should be entirely carried away by the coolant, therefore:

[0056] ;

[0057] in, Let $\frac{ ...

[0058] ;

[0059] Furthermore, the dimensional consistency of the physical quantities in the above heat balance equation is explained as follows: The dimension is watt. The dimension of is kilograms per cubic meter. The dimension is joules per kilogram per kelvin. The dimension of the product of the three is Kelvin, and the dimension of the product of the three is joules per cubic meter per second, which is the reciprocal of watts per cubic meter per second. Therefore The solution is in cubic meters per second, which is consistent with the physical meaning of volumetric flow rate, and no additional dimension conversion is required.

[0060] Step S303: Calculate the required flow rate for each intermediate flexible cable section in the same manner as in step S302. Flow rate required for the section connecting to the pile end :

[0061] ;

[0062] ;

[0063] Will , , Output the required flow rate of coolant for each section.

[0064] It should be noted that the above-mentioned coolant inlet temperature This represents the measured coolant temperature at the shared inlet manifold for all parallel branches. Since all parallel branches share the same inlet manifold, the coolant inlet temperature is consistent across all sections. .

[0065] It should be noted that the target temperature thresholds for each section mentioned above are the upper limits of the allowable steady-state operating temperature for each section. Each section can be set with different values ​​independently based on its material temperature resistance characteristics and safety margin. For example, the target temperature threshold for the gun head connector section... It can be lower than the target temperature threshold of the intermediate flexible cable section. This reflects the higher requirements for temperature control in the connector area.

[0066] In this embodiment, to avoid temperature exceeding the limit due to response lag when the current temperature of each segment is close to the target temperature threshold, a temperature margin compensation can be introduced into the heat balance equations in steps S302 and S303. Specifically, when the difference between the maximum value in the real-time temperature vector of a certain segment and the target temperature threshold of that segment is less than a preset margin threshold... At that time, the demand flow value of that section is multiplied by a margin factor greater than 1. Taking the gun head connector section as an example:

[0067] when At that time, the corrected demand flow is

[0068] ,in .

[0069] when hour, That is, no margin compensation is performed.

[0070] The intermediate flexible cable section and the pile-end connection section are judged and corrected in the same way. The corrected flow demand values ​​for each section replace the original flow demand values ​​for subsequent steps.

[0071] Furthermore, the aforementioned margin threshold This is a pre-calibrated temperature difference value, determined based on the maximum temperature rise the system may experience within a control cycle, to ensure that the temperature does not exceed the target temperature threshold before flow adjustment is performed in the next control cycle. Margin coefficient. It is a constant greater than 1, and its value is pre-calibrated based on the system's thermal inertia and the duration of the control cycle.

[0072] Step S4: Solve for the optimal opening command set of the electromagnetic proportional valves in each parallel branch.

[0073] The coolant flow rate demand values ​​for each section are input into the flow distribution optimization calculation module. With the goal of minimizing the total output power consumption of the liquid cooling pump, and with the constraint that the real-time temperature of each section does not exceed its independently set allowable upper limit temperature threshold, a quadratic programming algorithm is executed to solve and output the optimal opening command set of the electromagnetic proportional valves of each parallel branch.

[0074] Step S4 may specifically include:

[0075] Step S401: Define the optimization variable as the opening value of the solenoid proportional valve in each parallel branch. ,in , , The opening values ​​of the branch valves corresponding to the nozzle connector section, the intermediate flexible cable section, and the pile end connection section are respectively within the range of [missing information]. , This indicates transpose.

[0076] Step S402: Establish the mapping relationship between the valve opening degree of each branch and the volumetric flow rate of coolant through that branch. The relationship between the actual flow rate of each branch and the valve opening degree is expressed as follows:

[0077] ;

[0078] in, For the first The actual coolant volume flow rate of the branch circuit ; For the first Valve opening value for each branch; For the first The maximum flow rate when all branch valves are fully open is pre-calibrated based on the characteristics of each branch pipeline and the rated output capacity of the liquid cooling pump. The total flow rate of the liquid cooling pump is the sum of the flow rates of all branches.

[0079] ;

[0080] in, This represents the total flow rate of the liquid cooling pump. , , These are the actual coolant volume flow rates for the gun head connector section branch, the intermediate flexible cable section branch, and the pile end connection section branch, respectively.

[0081] Step S403: Establish the relationship between the total output power consumption and the total flow rate of the liquid cooling pump, and define the objective function as minimizing the total output power consumption of the liquid cooling pump:

[0082] ;

[0083] in, This represents the total output power consumption of the liquid cooling pump. , , The fitting coefficients for the power consumption characteristic function of the liquid-cooled pump are pre-calibrated from actual performance test data of the liquid-cooled pump and obtained by fitting a quadratic polynomial. This quadratic function form makes the objective function a convex quadratic function with respect to the optimization variables, satisfying the solution conditions of the quadratic programming algorithm.

[0084] Step S404: Establish constraints. The actual flow rate of each branch shall not be less than the coolant flow rate requirement of the corresponding section:

[0085] ;

[0086] The opening degree of each branch valve is within the effective range:

[0087] ;

[0088] Step S405: Substitute the actual flow expressions of each branch from step S402 into the objective function and constraints to transform the quadratic programming problem into one based on valve opening. To optimize the standard form of the variables. Specifically, the objective function expands to:

[0089] ;

[0090] in, , , These are the fitting coefficients for the power consumption characteristic function of the liquid-cooled pump. The flow constraint is transformed into a lower bound constraint on the valve opening:

[0091] ;

[0092] The above problem is a convex quadratic programming problem with linear inequality constraints. A quadratic programming algorithm is used to solve it, yielding the optimal valve opening value. As the optimal opening command set output for each parallel branch electromagnetic proportional valve, among which... This indicates transpose.

[0093] Furthermore, the optimal opening command set for the solenoid proportional valves in each of the above parallel branches... Each component in , , The values ​​are all within Within this range, the value directly corresponds to the opening percentage of each electromagnetic proportional valve. After receiving the opening percentage value, the built-in controller of the electromagnetic proportional valve converts it into a drive current signal for valve core displacement without the need for additional decoding or conversion operations.

[0094] In this embodiment of the application, in order to adjust the flow distribution in advance when the charging current undergoes a step change during fast charging, rather than passively responding after the temperature rises, the following step is included before step S405: obtaining the predicted value of the charging current for the next control cycle sent by the charging controller. ,based on The predicted heat generation power for each section is calculated according to step S2, and the predicted coolant flow rate for each section is calculated according to step S3. The larger of the current coolant flow rate and the predicted coolant flow rate is used as the lower limit of the flow rate constraint in step S404. This method allows the flow rate distribution to be adjusted before the actual current change occurs.

[0095] Furthermore, the above-mentioned predicted charging current value The target current value for the next stage is obtained by the charging controller based on the charging demand message sent by the battery management system, and it belongs to the existing data field in the charging communication protocol.

[0096] Step S5: Perform independent coolant flow distribution for each section.

[0097] The optimal opening command set of each parallel branch electromagnetic proportional valve is distributed to the electromagnetic proportional valve actuator corresponding to each parallel branch of the liquid cooling circuit, and the coolant flow of each independent branch of the nozzle connector section, intermediate flexible cable section and pile end connection section is adjusted respectively to achieve the matching of the coolant supply of each section with its actual heat load.

[0098] It should be noted that the above distribution process involves the thermal management control unit sending the opening command to the built-in controller of each electromagnetic proportional valve via the communication bus. Each electromagnetic proportional valve independently adjusts the valve core position according to the received opening command value, thereby changing the flow cross-sectional area of ​​its respective branch.

[0099] Step S6: Repeatedly execute dynamic flow redistribution adjustment.

[0100] With preset control cycle Steps S1 to S5 are executed repeatedly. At the beginning of each control cycle, the real-time temperature data and real-time charging current value of each temperature sensor are reacquired. The temperature vector generation, heat generation power calculation, demand flow calculation, quadratic programming solution and valve opening command issuance for each section are executed sequentially. The opening of the electromagnetic proportional valve for each section is updated to realize the dynamic flow redistribution and adjustment of the entire fast charging process.

[0101] It should be noted that the above-mentioned preset control cycle The time interval corresponding to one complete execution of steps S1 to S5 by the thermal management control unit is determined based on the time constant of the system temperature response.

[0102] In this embodiment of the application, in order to retain the operating data after the charging session ends for reference in subsequent charging sessions, the following steps are also included in step S6: after each control cycle is completed, the real-time temperature vector of each segment, the heat load dataset of each segment, the coolant demand flow value of each segment, and the optimal opening instruction set of each parallel branch electromagnetic proportional valve are stored in the non-volatile memory of the thermal management control unit according to the timestamp, forming the charging session thermal management log data.

[0103] On the other hand, the present invention also proposes a liquid-cooled thermal management system for a fast charging gun, comprising:

[0104] The temperature acquisition module is used to acquire real-time temperature data from multiple temperature sensors distributed along the entire length of the charging gun cable. The cable is divided into the gun head connector section, the intermediate flexible cable section, and the pile end connection section according to the physical location of the sensors. The temperature acquisition value corresponding to each section is extracted and a real-time temperature vector of each section is generated.

[0105] The heat load calculation module is used to obtain the real-time charging current value, combine it with the pre-stored resistance characteristic parameters of each section, calculate the real-time heating power of each section according to the Joule heating calculation model, and generate heat load datasets for each section.

[0106] The demand flow calculation module is used to calculate the minimum coolant volume flow rate required to maintain the temperature at its target temperature threshold in each section, based on the heat load dataset and real-time temperature vector of each section, and by substituting them into the heat balance equation of each section. This generates the coolant demand flow rate value for each section.

[0107] The flow distribution optimization module is used to perform a quadratic programming algorithm with the coolant demand flow rate of each section as the objective function and the temperature constraints of each section as the constraint condition, to solve and output the optimal opening command set of the electromagnetic proportional valves of each parallel branch.

[0108] The valve control execution module is used to distribute the optimal opening command set of the electromagnetic proportional valves in each parallel branch to the electromagnetic proportional valve actuators in each parallel branch, so as to realize the independent distribution of coolant flow in each section.

[0109] The cyclic scheduling module is used to trigger the temperature acquisition module, heat load calculation module, demand flow calculation module, flow allocation optimization module and valve control execution module to execute in sequence according to a preset control cycle, so as to realize dynamic flow redistribution and adjustment throughout the fast charging process.

[0110] By way of example, the system proposed in this invention may also include various features and combinations thereof in the method embodiments, which will not be elaborated here.

[0111] This invention reconstructs the liquid cooling circuit from a series structure to a parallel multi-segment independent branch structure. The coolant in each segment flows independently through the corresponding segment after being diverted from a common inlet manifold. The inlet temperature of the coolant in each branch is consistent and does not interfere with each other. From the circuit topology level, this invention eliminates the cumulative effect of the coolant temperature continuously rising after flowing through the upstream high-heat segment and the heat carrying capacity decreasing when it reaches the downstream segment in a series circuit. Therefore, it avoids the risk of local hot spots forming in the downstream segment due to the transfer of heat from the upstream to the downstream. Based on this parallel loop structure, distributed temperature data is collected for each section, real-time heat load and coolant flow demand are calculated independently, and a quadratic programming solution is performed with the goal of minimizing the total output power of the liquid cooling pump and the constraint that the temperature of each section does not exceed its respective allowable upper limit. This ensures that the coolant supply of each section is precisely matched to its actual heat dissipation demand. High heat density sections such as the gun head connector receive sufficient coolant flow, while the coolant supply of low heat load sections is reduced to the minimum level that meets the temperature constraints. This avoids the excess coolant flow and high power consumption of the liquid cooling pump caused by maintaining a high flow rate throughout the loop to meet the highest heat load section under a single flow control strategy. Thus, the operating power consumption of the liquid cooling pump is reduced while meeting the thermal safety requirements of all sections of the fast charging gun, alleviating the contradiction between the different heat dissipation requirements of each section and the system energy efficiency.

[0112] Application example:

[0113] A public charging station is equipped with 360kW DC fast charging piles. The charging gun cable is 5 meters long, and the liquid cooling circuit adopts a parallel three-branch structure. During a charging session, a pure electric vehicle connects to the charging pile, and the battery management system requests fast charging with a high current of 400A. After charging starts, the thermal management control unit cyclically adjusts the liquid cooling flow distribution according to a preset control cycle. The following uses a control cycle at the 15-minute mark of charging as an example to illustrate the data flow process of each step.

[0114] The charging gun cable has eight temperature sensors installed along its length: three at the gun head connector, three in the middle flexible cable section, and two at the charging terminal connection section. A coolant temperature sensor is located at the common inlet manifold of the liquid cooling circuit, and each of the three parallel branches is equipped with an electromagnetic proportional valve. The coolant used is a 1:1 volume ratio ethylene glycol aqueous solution.

[0115] The temperature acquisition module reads real-time data from eight temperature sensors and categorizes it into three sections based on the sensors' physical installation locations, generating a real-time temperature vector for each section. In the nozzle connector section, three sensors are arranged sequentially along the cable direction, and their collected values ​​form a temperature vector. The temperature vector is composed of the data collected by the three sensors in the middle flexible cable section. The temperature vector is composed of the data collected by two sensors in the pile end connection section. .

[0116] Table 1 Real-time temperature vectors for each section

[0117]

[0118] Table 2 Real-time temperature vector of pile end connection section

[0119]

[0120] The heat load calculation module obtains the real-time charging current value from the charging controller communication interface. A, and read the reference temperature of each segment from the pre-stored parameter table. The equivalent resistance value and the temperature coefficient of resistance of the conductor material are as follows. Since the current temperature in each section is significantly higher than the reference temperature, the module first calculates the arithmetic mean of the temperature vectors of each section as the representative temperature, then performs temperature correction on the equivalent resistance, and finally substitutes it into the Joule heating model to calculate the real-time heating power of each section.

[0121] The arithmetic mean of the temperature vectors for each section are as follows: This is the average value collected by the three sensors in the gun head connector section. This represents the average value collected by three sensors in the middle flexible cable section. This is the average value collected by two sensors in the pile end connection section. Corrected equivalent resistance. , , Substitute them separately Calculate the real-time heating power of each section.

[0122] Table 3 Resistance parameters and corrected heating power of each section

[0123]

[0124] The above heating power , , The heat load datasets for each section are compiled and transmitted to the demand flow calculation module.

[0125] The demand flow calculation module reads the preset target temperature threshold, coolant properties, and coolant inlet temperature for each section. It then substitutes the heat load dataset for each section into the steady-state heat balance equation to solve for the minimum required coolant volumetric flow rate for each section. (Coolant inlet temperature) These are measured values ​​at the shared inlet manifold. The target temperature threshold for each section is set independently based on the temperature resistance characteristics of its respective material. The target temperature threshold for the nozzle connector section is lower than that for the other two sections because of its concentrated contact resistance and higher temperature sensitivity.

[0126] Table 4 Input parameters and output results for demand flow calculation

[0127]

[0128] Based on this, the module further determines whether temperature margin compensation is triggered. Temperature vector of the nozzle connector section. The maximum value is 74.8. , and the target temperature threshold of 80 The difference is 5.2 Preset margin threshold 8 Since the temperature difference is less than the margin threshold, the nozzle connector section triggers margin compensation, and its required flow rate is multiplied by the margin coefficient. The corrected demand flow rate The maximum temperature vector in the intermediate flexible cable section is 54.6. With the target temperature threshold of 65 The difference is 10.4 The value exceeds the margin threshold, so compensation is not triggered. The maximum temperature vector in the pile end connection section is 41.2. With the target temperature threshold of 55 The difference is 13.8 Similarly, no compensation is triggered.

[0129] Table 5 Temperature margin compensation judgment results

[0130]

[0131] Corrected demand flow values ​​for each section , , Input traffic allocation optimization module.

[0132] The flow allocation optimization module first obtains the predicted charging current value for the next control cycle from the charging controller. A. This predicted value is derived from the target current value for the next stage in the charging demand message sent by the battery management system. The module calculates the current based on thermal load and demand flow rate. Calculate the predicted heat generation power and predicted coolant demand flow rate for each section, and use the larger of the current corrected demand flow rate and the predicted demand flow rate as the lower limit of the flow rate constraint.

[0133] Subsequently, the module reads the maximum flow rate when each branch valve is fully open. , , and the fitting coefficient of liquid cooling pump power consumption characteristics , , According to the valve opening degree To optimize variables, the total output power of the liquid cooling pump is used. Minimize as the objective function, with the actual flow rate of each branch not lower than the lower flow limit and the valve opening at... The constraints are within a certain range, and a quadratic programming algorithm is used to solve the problem.

[0134] Table 6 Input parameters for solving the quadratic programming problem

[0135]

[0136] The quadratic programming algorithm outputs the optimal valve opening command set. Because the heat load is highest in the nozzle connector section and temperature margin compensation is triggered, its branch valve opening is the largest; the heat load is lowest in the pile end connection section, and its branch valve opening is the smallest.

[0137] Table 7 Optimal Opening Command Set and Flow Allocation for Each Branch

[0138]

[0139] The above results indicate that the nozzle connector branch is allocated the largest share of the total flow, while the pile end connection branch is allocated only the minimum flow that meets the temperature constraint. The total flow of the three branches is 4.26 L / min, and the output power consumption of the liquid-cooled pump at this total flow is lower than that when the entire loop is driven at a single maximum flow.

[0140] After receiving the optimal opening command set, the valve control execution module sends each opening value to the built-in controller of the electromagnetic proportional valves in the three parallel branches via the communication bus. Each electromagnetic proportional valve independently adjusts its valve core position according to the received opening percentage value, changing the flow cross-sectional area of ​​its respective branch. This increases the coolant flow rate to 2.46 L / min in the nozzle connector branch, maintains it at 1.18 L / min in the intermediate flexible cable branch, and reduces it to 0.62 L / min in the pile-end connection branch. The coolant in the three branches is diverted from the common inlet manifold and flows independently through the corresponding heat exchange channels, absorbing heat from each section before converging into the common return manifold.

[0141] The cyclic scheduling module operates within a preset control cycle. Upon arrival, the temperature acquisition module is re-triggered to obtain the latest temperature data from each sensor, initiating a new round of heat load calculation, demand flow solution, secondary programming optimization, and valve opening update. After each control cycle is completed, the real-time temperature vector, heat load dataset, demand flow value, and optimal opening instruction set for each segment of the current cycle are stored in the non-volatile memory of the thermal management control unit according to the timestamp, forming the charging session thermal management log data.

[0142] Table 8. Trend of valve opening change during continuous control cycle

[0143]

[0144] The above data shows that when the charging current increases from 400 A to 420 A, the opening degree of the valves in all three branches increases accordingly to match the increased heat load; when the current drops to 380 A, the opening degree of each branch decreases, and the total flow rate of the liquid cooling pump decreases accordingly. Since the predicted current value of 420 A for the next cycle was obtained through feedforward in the 30th cycle, the lower limit of the flow rate of the nozzle connector branch in the 30th cycle was determined in advance according to the required flow rate corresponding to 420 A. Therefore, when the current actually increases in the 31st cycle, the temperature of each section does not fluctuate beyond the limit.

[0145] In the above implementation process, data starts from the raw acquisition values ​​of temperature sensors, is grouped into segments to generate temperature vectors for each segment, and then, after temperature correction based on charging current and resistance parameters, the real-time heat generation power of each segment is calculated. The heat generation power of each segment, along with the target temperature threshold and coolant properties, is substituted into the heat balance equation to obtain the required flow rate. The required flow rate, after temperature margin compensation and current feedforward correction, is used as a constraint input into a quadratic programming model. The quadratic programming model solves for the optimal valve opening of each branch with the objective of minimizing the power consumption of the liquid cooling pump. Finally, the valve opening command is issued to the actuator to complete the flow distribution. The entire data link, from physical quantity acquisition, heat load estimation, flow demand solution to optimization decision-making and execution control, is sequentially connected, and is updated cyclically in each control cycle, forming a closed-loop dynamic adjustment. The changing trends of temperature data, heat generation power, required flow rate, and valve opening of each segment during the cycle are interrelated, reflecting the adaptive adjustment capability of independent flow distribution of multiple parallel branches under different heat load conditions.

[0146] The embodiments of the present invention have been described above. However, the embodiments are not limited to the specific implementation methods described above. The specific implementation methods described above are merely illustrative and not restrictive. Those skilled in the art can make more equivalent embodiments under the guidance of the present embodiments, and all of them are within the protection scope of the present embodiments.

Claims

1. A method for controlling the liquid cooling and heating of a fast charging gun, characterized in that, Includes the following steps: The real-time temperature data of multiple temperature sensors distributed along the charging gun cable is acquired, and the cable is divided into the gun head connector section, the intermediate flexible cable section and the pile end connection section, and a real-time temperature vector of each section is generated. The real-time charging current value is obtained, and combined with the pre-stored resistance characteristic parameters of each section, the real-time heating power of each section is calculated according to the Joule heating calculation model to generate a heat load dataset for each section. Based on the heat load dataset and real-time temperature vector of each section, the minimum coolant volume flow rate required to maintain the temperature at its respective target temperature threshold in each section is calculated by substituting the heat balance equation of each section into the heat balance equation of each section, and the coolant demand flow rate value of each section is generated. With the objective function of minimizing the total output power consumption of the liquid cooling pump and the constraint that the actual flow rate of each section is not lower than the corresponding coolant demand flow rate, a quadratic programming algorithm is executed to solve for the optimal opening command set of the electromagnetic proportional valves in each parallel branch. The optimal opening instruction set is distributed to the electromagnetic proportional valves corresponding to each parallel branch of the liquid cooling circuit, and the coolant flow rate of each independent branch is adjusted respectively.

2. The fast charging gun liquid cooling and heating management control method according to claim 1, characterized in that, The real-time temperature vector for each section is a one-dimensional numerical sequence composed of the collected values ​​of all temperature sensors in that section, arranged in the physical order of the sensors along the cable direction.

3. The fast charging gun liquid cooling and heating management control method according to claim 1, characterized in that, The calculation of the real-time heating power of each section according to the Joule heating calculation model includes: Read the equivalent resistance value of each section, where the equivalent resistance value is the equivalent total resistance after combining the DC resistance of the conductor and the contact resistance within that section; The real-time heating power of each section is equal to the product of the square of the real-time charging current and the equivalent resistance of the corresponding section.

4. The fast charging gun liquid cooling and heating management control method according to claim 3, characterized in that, The equivalent resistance value of each section is temperature corrected based on the arithmetic mean of all sensor data collected in the real-time temperature vector of each section. The correction method is to multiply the original equivalent resistance value by a temperature correction factor, which is equal to the sum of 1 and the product of the conductor material resistance temperature coefficient and the difference between the arithmetic mean temperature of the section and the reference temperature. The corrected equivalent resistance value is substituted into the Joule heating calculation model instead of the original equivalent resistance value.

5. The fast charging gun liquid cooling and heating management control method according to claim 1, characterized in that, The calculation of the minimum coolant volume flow rate required to maintain the temperature at its respective target temperature threshold in each section includes: Obtain the preset target temperature threshold, specific heat capacity, density, and inlet temperature of the coolant for each section; A steady-state heat balance equation is established for each section. The required volumetric flow rate of coolant for each section is equal to the real-time heat generation power of that section divided by the product of the coolant density, specific heat capacity, and the target temperature threshold of that section minus the difference between the coolant inlet temperature. The target temperature threshold for each section is the upper limit of the allowable steady-state operating temperature for each section, and different values ​​are set independently for each section.

6. The fast charging gun liquid cooling and heating management control method according to claim 5, characterized in that, When the difference between the maximum value in the real-time temperature vector of a certain section and the target temperature threshold of that section is less than a preset margin threshold, the demand flow value of that section is multiplied by a margin coefficient greater than 1 to obtain the corrected demand flow value; when the difference is not less than the margin threshold, the demand flow value of that section is not corrected.

7. The fast charging gun liquid cooling and heating management control method according to claim 1, characterized in that, The execution of the quadratic programming algorithm includes: The optimization variable is defined as the opening value of the electromagnetic proportional valve of each parallel branch, and the actual coolant volume flow rate of each branch is equal to the product of the valve opening value of that branch and the maximum flow rate when the valve of that branch is fully open. The total flow rate of the liquid cooling pump is the sum of the actual flow rates of each branch. The objective function is a quadratic polynomial of the total output power of the liquid cooling pump with respect to the total flow rate. The fitting coefficient of the quadratic polynomial is obtained by pre-calibrating the performance test data of the liquid cooling pump. The constraints include that the actual flow rate of each branch is not less than the coolant demand flow rate of the corresponding section, and that the valve opening value of each branch is within the range of zero to one. Substitute the actual flow expressions of each branch into the objective function and constraints to solve the convex quadratic programming problem with linear inequality constraints, and obtain the optimal valve opening value.

8. The liquid cooling and heating management control method for fast charging guns according to claim 7, characterized in that, Before executing the quadratic programming algorithm, the following steps are also included: Obtain the predicted charging current value for the next control cycle sent by the charging controller, and calculate the predicted heat generation power and predicted coolant flow rate for each section based on the predicted charging current value. The larger of the current coolant demand flow rate value for each section and the predicted coolant demand flow rate value is used as the lower limit of the flow rate in the constraint condition.

9. The liquid cooling and heating management control method for fast charging guns according to claim 1, characterized in that, The steps of obtaining the real-time temperature vector of each section, calculating the real-time heat generation power of each section, calculating the coolant demand flow rate of each section, solving for the optimal opening instruction set, and distributing the optimal opening instruction set are executed cyclically with a preset control cycle. After each control cycle is completed, the real-time temperature vector of each segment, the heat load dataset of each segment, the coolant demand flow value of each segment, and the optimal opening instruction set of the current cycle are stored in non-volatile memory according to the timestamp, forming the charging session thermal management log data.

10. A liquid cooling and heating management system for a fast charging gun, used to execute the liquid cooling and heating management control method for a fast charging gun according to any one of claims 1 to 9, characterized in that, include: The temperature acquisition module is used to acquire real-time temperature data from multiple temperature sensors distributed along the charging gun cable, divide the cable into the gun head connector section, the intermediate flexible cable section and the pile end connection section, and generate real-time temperature vectors for each section. The heat load calculation module is used to obtain the real-time charging current value, combine it with the pre-stored resistance characteristic parameters of each section, calculate the real-time heating power of each section according to the Joule heating calculation model, and generate heat load datasets for each section. The demand flow calculation module is used to calculate the minimum coolant volume flow rate required for each section to maintain the temperature at its respective target temperature threshold based on the heat load dataset and real-time temperature vector of each section, and to generate the coolant demand flow rate value of each section. The flow distribution optimization module is used to minimize the total output power consumption of the liquid cooling pump as the objective function and with the constraint that the actual flow rate of each section is not lower than the corresponding coolant demand flow rate, and to execute a quadratic programming algorithm to solve for the optimal opening instruction set of the electromagnetic proportional valves of each parallel branch. The valve control execution module is used to distribute the optimal opening instruction set to the electromagnetic proportional valves corresponding to each parallel branch of the liquid cooling circuit, and adjust the coolant flow rate of each independent branch. The cyclic scheduling module is used to trigger the temperature acquisition module, heat load calculation module, demand flow calculation module, flow allocation optimization module and valve control execution module to execute in sequence according to a preset control cycle, so as to realize dynamic flow redistribution and adjustment throughout the fast charging process.

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