Multi-target-based performance coordination optimization control method for thermal management system of pure electric vehicle

Abstract

The invention provides a multi-target-based performance coordination optimization control method for a thermal management system of a pure electric vehicle, and solves the problems of vehicle system performance optimization priority and coordination of different sub-controllers caused by multi-parameter change under specific working conditions. Comprising the following steps: 1, selecting an air conditioner air outlet temperature, a battery cold plate water outlet temperature and a driving motor rotor temperature respectively corresponding to the thermal comfort of a vehicle passenger compartment, the thermal reliability of a power battery and the thermal stability of the driving motor, and calculating a comprehensive evaluation coefficient K; 2, calculating a corresponding Shannon entropy value, and determining target performance needing to be optimized of the system according to the comprehensive evaluation coefficient K and the Shannon entropy value; step 3, determining priorities corresponding to different performances according to the target performance needing to be optimized of the system and the system priority coefficient; and step 4, calculating the optimization time TOP of the system performance among different sub-controllers, and then activating the corresponding controllers in sequence in combination with the priorities to realize the multi-objective optimization control of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal management control of new energy vehicles, and in particular to a performance coordinated optimization control method of a thermal management system of a pure electric vehicle based on multiple objectives. Background Art

[0002] During the driving process of the vehicle, the external environmental variables and the driving conditions of the vehicle are accompanied by the response process of the thermal management system, which is also accompanied by the dynamic changes of system parameters. Different thermal management system parameters correspond to different changes in system performance.

[0003] The current research and results on thermal management systems lack performance requirements based on vehicle status data, and also lack quantitative judgment and analysis of optimization priorities based on this data. In addition, for the selection and calculation of sub-controller action time intervals, most applications tend to rely on empirical calculations, and lack the corresponding calculation formulas for reasonable quantification. How to optimize control through quantitative indicators and which performance indicators should be optimized first are issues that need to be solved urgently. Summary of the invention

[0004] The present invention proposes a performance coordinated optimization control method for a pure electric vehicle thermal management system based on multiple objectives, which solves the problem of vehicle system performance optimization priority and coordination of different sub-controllers caused by multi-parameter changes under specific working conditions.

[0005] The present invention is achieved through the following technical solutions.

[0006] A multi-objective pure electric vehicle thermal management system performance coordinated optimization control method includes the following steps:

[0007] Step 1: Select the air-conditioning outlet temperature T corresponding to the thermal comfort of the vehicle passenger compartment, the thermal reliability of the power battery, and the thermal stability of the drive motor. cab , Battery cold plate outlet temperature T bat and the drive motor rotor temperature T mot , calculate the comprehensive evaluation coefficient K;

[0008] Step 2: Calculate T cab , T bat and T mot The corresponding Shannon entropy values ​​are En1, En2 and En3 respectively, and the target performance that needs to be optimized of the system is determined according to the comprehensive evaluation coefficient K and the Shannon entropy value obtained in step 1;

[0009] Step 3: According to the target performance to be optimized by the system obtained in step 2 and the system priority coefficient Γj, the priority level corresponding to different performances is established;

[0010] Step 4: Calculate the optimization time T of the system performance between different sub-controllers OP , and then activate the controllers A’, B’, and C’ corresponding to the target performances A, B, and C in sequence according to the priorities, so as to realize the multi-objective optimal control of the system.

[0011] Beneficial effects of the present invention:

[0012] 1. By selecting the three performances of the thermal comfort of the required passenger compartment, the thermal reliability of the power battery, and the thermal stability of the drive motor, and then selecting the corresponding known external environmental variables and vehicle state parameters for quantitative calculation and parameter analysis, the present invention realizes the optimization and control of the performance of the thermal management system within the time interval under the current working conditions;

[0013] 2. The present invention effectively utilizes the current existing external environmental variable and vehicle state parameter data for quantitative system identification and performance determination;

[0014] 3. In the present invention, the calculation of the system time delay coefficient Ψ further considers the influence of the system response transmission speed and the communication network lag time Δ, and corrects the system time delay coefficient Ψ;

[0015] 4. The present invention has the characteristics of easy acquisition of parameters, fast online calculation speed, high-efficiency coordinated control, and accurate performance optimization. Description of the drawings

[0016] Figure 1 It is the schematic diagram of the performance optimization control of the multi-objective pure electric vehicle thermal management system according to the present invention. Detailed implementation manners

[0017] The following will describe in detail the exemplary embodiments of the present invention with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the drawings are only exemplary, intended to explain the principles and spirit of the present invention, and not to limit the scope of the present invention.

[0018] As Figure 1 shown, a method for coordinated optimization control of the performance of a multi-objective pure electric vehicle thermal management system according to the present invention specifically includes the following steps:

[0019] Step 1: Select the air outlet temperature T of the air conditioner corresponding to the thermal comfort of the vehicle passenger compartment, the water outlet temperature T of the battery cold plate, and the rotor temperature T of the drive motor respectively cab , calculate the comprehensive evaluation coefficient K, and the specific formula is as follows: bat and the rotor temperature T of the drive motor mot , and calculate the comprehensive evaluation coefficient K. The specific formula is as follows:

[0020]

[0021] In the formula, T target, T bat，max and T mot，max are respectively the limit values of T cab , T bat and T mot . The actual correction coefficients corresponding to T cab , T bat and T mot are μ1, μ2 and μ3 respectively. During specific implementation, the value ranges are respectively:

[0022]

[0023] In this embodiment, T target is the target temperature of the occupant compartment, taking 25 - 28°C in summer and 15 - 18°C in winter; T bat，max is the maximum operating temperature parameter of the battery, generally taking 60°C; T mot，max is the common insulation material grade and allowable maximum operating temperature of the motor and controller, Y - grade 90, A - grade 105, E - grade 120, B - grade 130, F - grade 155, H - grade 180, C - grade above 180°C.

[0024] Step 2: Calculate the Shannon entropy values respectively corresponding to T cab , T bat and T mot as En1, En2 and En3 respectively, and determine the target performance to be optimized for the system according to the comprehensive evaluation coefficient K obtained in Step 1 and the Shannon entropy values;

[0025] The specific calculation method of the entropy value is as follows:

[0026] En i =-P(x i )log2P(x i ), i = 1, 2, 3

[0027] In the formula, P(x i ) is the probability of the state x i appearing. x i corresponds to the state variables T cab , T bat and T mot respectively.

[0028] In this embodiment, Table 1 below is used to determine the target performance to be optimized for the system:

[0029] Table 1 Determination of System Performance Optimization Requirements

[0030]

[0031] In the table, A, B, and C respectively represent the thermal comfort of the passenger compartment, the thermal reliability of the power battery, and the thermal stability of the drive motor. 1 and 0 respectively indicate the need for optimization and no need for optimization, En 1max 、En 2max and En 3max respectively represent the maximum values corresponding to the state entropy values of each state.

[0032] Step 3: Determine the priority levels of different performances according to the target performance that needs to be optimized in the system and the system priority coefficient Γj obtained in Step 2; specifically, the following steps are adopted: Set priorities 1, 2, and 3 to correspond to high, medium, and low priorities respectively;

[0033] 3.1 When a certain target performance among the thermal comfort A of the passenger compartment, the thermal reliability B of the power battery, and the thermal stability C of the drive motor needs to be optimized, that is, on the premise of A = 1, B = 0 and C = 0, or A = 0, B = 1 and C = 0, or A = 0, B = 0 and C = 1, at this time the priority of this performance is 1, corresponding to the highest;

[0034] 3.2 When two of the target performances among the thermal comfort A of the passenger compartment, the thermal reliability B of the power battery, and the thermal stability C of the drive motor need to be optimized, that is, on the premise of A = 1, B = 1 and C = 0, or A = 0, B = 1 and C = 1, or A = 1, B = 0 and C = 1, at this time the priority of the system performance needs to be further determined, specifically as follows:

[0035] i = A,B or B,C or A,C

[0036] 3.3 When all three target performances among the thermal comfort A of the passenger compartment, the thermal reliability B of the power battery, and the thermal stability C of the drive motor need to be optimized, that is, on the premise of A = 1, B = 1 and C = 1, at this time the priority of the system performance needs to be further determined; among them, the system performance corresponding to system priority 1 is as follows:

[0037] Priority 1: max(En i ) → i, i → A, or B, or C

[0038] On this basis, continue to determine priorities 2 and 3, and calculate the evaluation coefficient K of the remaining two performances except for the highest priority j as follows:

[0039]

[0040] At this time, further calculate the system priority coefficient Γ j of different performance optimizations, then there is:

[0041] i = 1,2,3, j = A,B,C

[0042] If performance A corresponds to priority 1, then priorities 2 and 3 are respectively:

[0043] If performance B corresponds to priority 1, then priorities 2 and 3 are respectively:

[0044]

[0045] If performance C corresponds to priority 1, then priorities 2 and 3 are respectively:

[0046]

[0047] Step 4: Calculate the optimization time T of the system performance between different sub - controllers OP , and then activate the controllers A', B', and C' corresponding to the target performances A, B, and C in sequence according to the priorities to achieve the multi - objective optimal control of the system;

[0048] In this embodiment, the optimization time T of the sub - controller OP has the following formula:

[0049] T OP = ψT C

[0050] In the formula, Ψ is the system time delay coefficient, and T C is the control period of the controller.

[0051] Specifically, when implementing, the calculation of the system time delay coefficient Ψ further considers the influence of the system response transmission speed and the communication network lag time Δ. Therefore, the system time delay coefficient Ψ is corrected, and the formula is as follows:

[0052]

[0053] In the formula, N is the total number of control instructions, L C is the length of the control instruction, v C is the sending speed of the control instruction, B L is the bus load rate at the current moment, and λ is the fluctuation coefficient corresponding to the instruction transmission speed v C , and in this embodiment, the value range is [0.8, 0.98].

[0054] In summary, the above is only a preferred embodiment of the present invention and is not used to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0055] For those skilled in the art, it is obvious that the embodiments of the present invention are not limited to the details of the above-mentioned exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the embodiments of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the embodiments of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the embodiments of the present invention. Any reference signs in the claims should not be construed as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units, modules or devices described in the system, apparatus or terminal claims can also be implemented by the same unit, module or device through software or hardware. The words such as "first" and "second" are used to indicate names and do not represent any specific order.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention and not to limit them. Although the embodiments of the present invention have been described in detail with reference to the above preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the embodiments of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A performance coordinated optimization control method for a thermal management system of a pure electric vehicle based on multiple objectives, characterized in that: The following steps are involved: Step 1: Select the air-conditioning outlet temperature T corresponding to the thermal comfort of the vehicle passenger compartment, the thermal reliability of the power battery, and the thermal stability of the drive motor. cab , Battery cold plate outlet temperature T bat and the drive motor rotor temperature T mot , calculate the comprehensive evaluation coefficient K; Step 2: Calculate T cab 、T bat and T mot The corresponding Shannon entropy values ​​are En1, En2 and En3 respectively, and the target performance that needs to be optimized of the system is determined according to the comprehensive evaluation coefficient K and the Shannon entropy value obtained in step 1; Step 3: According to the target performance to be optimized by the system obtained in step 2 and the system priority coefficient Γj, the priority level corresponding to different performances is established; Step 4: Calculate the optimization time T of system performance between different sub-controllers OP , and then activate the controllers A', B', and C' corresponding to the target performance A, B, and C in turn according to the priority to achieve multi-objective optimization control of the system.

2. The method for coordinated optimization control of the thermal management system performance of a multi-objective pure electric vehicle according to claim 1, characterized in that: The calculation formula of the comprehensive evaluation coefficient K is as follows: Where, T target 、T bat，max and T mot，max T cab 、T bat and T mot The limit value, T cab 、T bat and T mot The corresponding actual correction coefficients are μ1, μ2 and μ3 respectively.

3. The method for coordinated optimization control of the thermal management system performance of a multi-objective pure electric vehicle according to claim 2, characterized in that: The actual correction coefficients μ1, μ2 and μ3 have value ranges of:

4. A method for coordinated optimization control of thermal management system performance of a multi-objective pure electric vehicle as claimed in claim 1, 2 or 3, characterized in that: The entropy value is calculated as follows: En i =-P(x i )log2P(x i ),i=1,2,3 In the formula, P(x i ) is the state x i The probability of occurrence, x i Corresponding to the state quantity T cab 、T bat and T mot .

5. The method for coordinated optimization control of thermal management system performance of a multi-objective pure electric vehicle according to claim 4, characterized in that: Use the following Table 1 to determine the target performance that needs to be optimized for the system: Table 1 Determination of system performance optimization requirements In the table, A, B and C represent the thermal comfort of the passenger compartment, the thermal reliability of the power battery and the thermal stability of the drive motor, respectively. 1 and 0 represent the need for optimization and no need for optimization, respectively. 1max 、En 2max and En 3max They represent the maximum value corresponding to each state entropy value.

6. The method for coordinated optimization control of thermal management system performance of a multi-objective pure electric vehicle according to claim 4, characterized in that: Step 3 is as follows: Set priorities 1, 2, and 3 to correspond to high, medium, and low priorities respectively; 3.1 When one of the target performances among passenger compartment thermal comfort A, power battery thermal reliability B, and drive motor thermal stability C needs to be optimized, that is, when A=1, B=0, and C=0, or when A=0, B=1, and C=0, or when A=0, B=0, and C=1, the priority of the performance is 1, which corresponds to the highest; 3.2 When two of the target performances among passenger compartment thermal comfort A, power battery thermal reliability B, and drive motor thermal stability C need to be optimized, that is, under the premise of A=1, B=1, and C=0, or under the premise of A=0, B=1, and C=1, or under the premise of A=1, B=0, and C=1, the priority of system performance needs to be further determined, as follows: 3.3 When all three target performances of passenger compartment thermal comfort A, power battery thermal reliability B, and drive motor thermal stability C need to be optimized, that is, under the premise of A=1, B=1, and C=1, the priority of system performance needs to be further determined; the system performance corresponding to system priority 1 is as follows: Priority 1: max(En i )→i,i→A, or B, or C On this basis, continue to determine priorities 2 and 3, and calculate the evaluation coefficients K of the remaining two performances except the highest priority. j As shown below: At this point, the system priority coefficients Γj of different performance optimizations are further calculated, and we have: Γ j =K j In i ,i=1,2,3,j=A,B,C If performance A corresponds to Priority 1, then priorities 2 and 3 are: If performance B corresponds to priority 1, then priorities 2 and 3 are: If performance C corresponds to priority 1, then priorities 2 and 3 are:

7. A method for coordinated optimization control of thermal management system performance of a multi-objective pure electric vehicle as claimed in claim 1 or 2 or 3 or 5 or 6, characterized in that: The optimization time T of the sub-controller OP The formula is as follows: Where Ψ is the system time delay coefficient, T C is the control period of the controller.

8. The method for coordinated optimization control of the thermal management system performance of a multi-objective pure electric vehicle according to claim 7, characterized in that: The calculation of the system time delay coefficient Ψ further considers the influence of the system response transmission speed and the communication network hysteresis time Δ, so the system time delay coefficient Ψ is corrected, and the formula is as follows: Where N is the total number of control instructions, L C is the length of the control instruction, v C To control the speed of sending instructions, B L is the bus load rate at the current moment, λ is the instruction transmission speed v C The corresponding volatility coefficient.

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