An intelligent optimization management system for new energy heavy truck logistics

Abstract

The present invention discloses an intelligent optimization management system for logistics of new energy heavy trucks, which relates to the field of battery management, including a static battery pack transmitting end voltage signal analysis execution module and a dynamic battery pack receiving end voltage signal monitoring module; the new energy heavy truck logistics intelligent optimization management system, the present invention provides an intelligent optimization management system for logistics of new energy heavy trucks, which cooperates with each other through a dynamic voltage receiving end voltage strength acquisition unit and a dynamic voltage receiving end voltage signal strength measurement and analysis unit, and accurately feeds back the voltage strength parameters of the battery pack receiving end through a voltage sensor and scientifically compares them with the receiving end voltage strength threshold, thereby realizing accurate monitoring of the battery pack measurement receiving end voltage strength characteristics and accurate feedback of the battery pack voltage measurement process; the battery pack temperature control operation result judgment processing unit accurately monitors the temperature control operation results of the battery pack temperature control system, and improves the precise temperature control of the battery pack operation system.

Description

Technical Field

[0001] The present invention relates to battery management technology, and in particular to an intelligent optimization management system for logistics of new energy heavy trucks. Background Art

[0002] New energy heavy-duty trucks are heavy-duty trucks powered by clean energy and are a type of new energy vehicle. In recent years, with rising environmental awareness and adjustments to energy mix, the new energy heavy-duty truck industry has experienced rapid growth. However, this development also faces challenges, one of which is a shortage of charging infrastructure. The insufficient number of charging stations and slow charging speeds are hindering the industry's development. Therefore, to meet the charging needs of new energy heavy-duty trucks and improve their operational efficiency, a mobile charging management and control system for new energy heavy-duty trucks is crucial.

[0003] Currently, electric vehicle battery packs are generally developing toward longer battery life (high energy density) and faster charging (high charge rate). As the energy density of battery pack systems increases, the gaps between cells become narrower, and the heat dissipation area is extremely limited. Limited by the performance of key heat transfer components, current practical battery management technologies struggle to balance battery pack energy density and battery management performance, contributing to the frequent spontaneous combustion of electric vehicles. Existing literature generally over-idealizes battery management: the rigid, tight fit between the battery and the metal heat transfer component presents practical engineering challenges such as excessive thermal resistance, loss of thermal grease, wear of the battery casing, and insulation.

[0004] However, during the current system installation and use, electronic components usually integrate various high-frequency circuits, digital circuits and analog circuits, and generate a large amount of electromagnetic waves during operation. Therefore, the electronic components and other electronic components will generate electromagnetic interference (EMI) with each other, which not only affects the function of the electronic components, but also causes circuit heating problems. Therefore, precise battery pack temperature control is required. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent optimization management system for logistics of new energy heavy trucks to solve the above-mentioned deficiencies in the prior art.

[0006] In order to achieve the above-mentioned purpose, the present invention provides the following technical solution: an intelligent optimization management system for new energy heavy truck logistics, comprising the following steps:

[0007] S1. Collect battery pack ambient temperature data and battery pack ambient electromagnetic intensity data;

[0008] S2. Perform data preprocessing on the battery pack ambient temperature data and the ambient electromagnetic intensity data, and generate standard battery pack ambient temperature data and standard battery pack ambient electromagnetic intensity data;

[0009] S3. Use a data recognition algorithm to analyze and match the standard battery pack ambient temperature data and the standard battery pack ambient electromagnetic intensity data, respectively, to construct and output the specific standard electromagnetic intensity interval data of the static voltage transmitter;

[0010] S4, executing the operation of transmitting a temperature control signal from the static voltage transmitting end according to the specific standard electromagnetic intensity interval data of the static voltage transmitting end;

[0011] S5. When the static voltage transmitting end transmits a temperature control signal, collecting voltage intensity data of the dynamic voltage receiving end;

[0012] S6. Comparing the voltage strength data of the dynamic voltage receiving end with the voltage strength threshold data of the dynamic voltage receiving end, and analyzing and constructing a voltage signal strength measurement result of the dynamic voltage receiving end based on the voltage strength comparison result of the dynamic voltage receiving end;

[0013] S7. Analyze and determine battery pack temperature control operation result data based on the voltage signal strength measurement result of the dynamic voltage receiving terminal and process the data.

[0014] Furthermore, the S1 includes the following steps:

[0015] S11. Collecting the temperature of the environment in which the liquid-cooled power battery pack is located online through a temperature sensor and generating battery pack ambient temperature data, where the battery pack ambient temperature data is in degrees Celsius;

[0016] S12. Collect the electromagnetic intensity of the battery pack's environment online through an electromagnetic intensity measuring instrument and generate battery pack environment electromagnetic intensity data, where the unit of the battery pack environment electromagnetic intensity data is Tesla / meter.

[0017] Furthermore, the step S2 includes the following steps:

[0018] An adaptive filtering method is used to perform data noise reduction preprocessing on the battery pack ambient temperature data and the battery pack measured ambient electromagnetic intensity data, respectively. After the data noise reduction preprocessing, standard battery pack measured ambient temperature data and standard battery pack ambient electromagnetic intensity data are generated. The unit of the standard battery pack measured ambient temperature data is Celsius, and the unit of the standard battery pack ambient electromagnetic intensity data is Tesla / meter.

[0019] Furthermore, the step S3 includes the following steps:

[0020] S31, obtaining the standard battery pack environment temperature data and the standard battery pack environment electromagnetic intensity data;

[0021] S32. Establishing a data set of standard ambient temperature and electromagnetic intensity intervals at the static voltage transmitter

[0022]

[0023] in T n Indicates the standard ambient temperature range of the nth static voltage transmitter. Indicates the maximum value of the standard ambient temperature range of the static voltage transmitter, the standard ambient temperature range of the static voltage transmitter is T1 to The corresponding ambient temperature values ​​increase in sequence; m1=1,2,3,…,θ1, represents the m1th static voltage transmitter standard electromagnetic intensity interval data corresponding to the static voltage transmitter standard ambient temperature interval T1, θ1 represents the maximum number of static voltage transmitter standard electromagnetic intensity interval data corresponding to the static voltage transmitter standard ambient temperature interval T1, The unit is Tesla / meter; m n =1,2,3,…,θ n , Indicates the mth corresponding to the standard ambient temperature range Tn of the static voltage transmitter n The standard electromagnetic intensity interval data of the static voltage transmitting end, θ n Indicates the maximum value of the number of data in the standard electromagnetic intensity interval of the static voltage transmitter corresponding to the standard ambient temperature interval Tn of the static voltage transmitter. The unit is Tesla / meter; Indicates the standard ambient temperature range of the static voltage transmitter The corresponding The standard electromagnetic intensity interval data of the static voltage transmitting end, Indicates the standard ambient temperature range of the static voltage transmitter The maximum value of the corresponding static voltage transmitter standard electromagnetic intensity interval data quantity, The unit is Tesla / meter;

[0024] S33, using a data recognition algorithm to identify the standard battery pack measured ambient temperature data, the standard battery pack ambient electromagnetic intensity data and the static voltage transmitter standard ambient temperature and electromagnetic intensity interval data set. nAnd static voltage transmitter standard electromagnetic intensity interval data The standard electromagnetic intensity interval data of the static voltage transmitter is matched based on the temperature data and electromagnetic intensity data. The standard electromagnetic intensity interval data of the static voltage transmitter matched by the data recognition algorithm Perform matching scoring, which specifically includes the following steps:

[0025] E1, filters out useless features in the finished model vector feature information, uses the sigmoid activation function as the gate state, and then performs a dot product with the finished model vector feature, and then uses the tanh activation function to obtain the gate unit feature screening;

[0026] E2, use the attention mechanism to strengthen the key vector feature information in the electromagnetic intensity interval database, and obtain the embedding vector t and the feature representation of the text according to the vector feature type. Through tT, each feature in the text is scored to perceive the important information in the text, as shown in the following formula:

[0027]

[0028] Where ɑk represents the feature score, m represents the number of features, d represents the dth feature, and tT represents the feature vector parameter;

[0029] E3, the electromagnetic intensity interval database after evaluation can be expressed as H' att , as shown below:

[0030]

[0031] where H′ att =[h′1, h′2, h′3...h′ m ], α=[α1, α2, α3...α m ] is the attention vector, is the vector matrix of the electromagnetic intensity interval database;

[0032] E4, query representation is obtained by the vector feature information fusion module and the characteristic representation H′ of the electromagnetic intensity interval database att =[h′1, h′2, h′3...h′ m ], and then calculate it by the maximum similarity, through and H′ attThe score between the queried electromagnetic intensity interval data and the electromagnetic intensity interval database can be calculated, which is the sum of the maximum similarities represented by each finished product model vector queried and each electromagnetic intensity interval data working vector in the electromagnetic intensity interval database, as shown in the following formula:

[0033]

[0034] in Indicates that there are m query results to be matched, H′ att Indicates that the electromagnetic intensity interval database has n features, Indicates the i-th query result to be matched, h′ j represents the jth feature in the electromagnetic intensity interval database;

[0035] S34, all the static voltage transmitter standard electromagnetic intensity interval data output from step S33 Identify and generate specific standard electromagnetic intensity interval data of the static voltage transmitting end and establish a specific standard electromagnetic intensity interval data set of the static voltage transmitting end;

[0036] S35. Output the generated specific standard electromagnetic intensity interval data set of the static voltage transmitting end.

[0037] Furthermore, the S4 includes the following steps:

[0038] The temperature control signal transmission operation is performed at the static voltage transmitting end of the battery pack in order according to the specific standard electromagnetic intensity interval data of the static voltage transmitting end in the specific standard electromagnetic intensity interval data set according to the magnitude of the electromagnetic intensity values.

[0039] Furthermore, the S5 includes the following steps:

[0040] When the static voltage transmitting end of the battery pack performs the operation of transmitting the temperature control signal, the voltage of the dynamic receiving end of the battery pack is collected online through the voltage sensor to receive the induced voltage intensity generated by the static voltage transmitting end performing the operation of transmitting the temperature control signal, and the induced voltage intensity is marked to generate the dynamic voltage receiving end voltage intensity data V, where V is in volts.

[0041] Furthermore, the S6 includes the following steps:

[0042] S61: Establish voltage intensity threshold data VD for a dynamic voltage receiving terminal, wherein the voltage intensity threshold data VD represents the minimum voltage intensity data received by the dynamic voltage receiving terminal for the battery pack to normally perform battery temperature control operations, and the unit of VD is volts.

[0043] S62: Compare the voltage strength data V of the dynamic voltage receiving end with the voltage strength threshold data VD of the dynamic voltage receiving end, and analyze and construct a voltage signal strength measurement result of the dynamic voltage receiving end based on the voltage strength comparison result of the dynamic voltage receiving end;

[0044] When V≥VD, it means that the voltage strength received by the dynamic voltage receiving end meets the normal temperature control operation of the battery pack, and the voltage signal strength measurement result of the output dynamic voltage receiving end is satisfied;

[0045] When V<VD, it means that the voltage strength received by the dynamic voltage receiving end does not meet the normal temperature control operation of the battery pack, and the measurement result of the voltage signal strength of the dynamic voltage receiving end is output as unsatisfactory.

[0046] Furthermore, the S7 includes the following steps:

[0047] When the voltage signal strength measurement result of the dynamic voltage receiving end is satisfied, the battery pack temperature control operation result data indicates that the battery pack has completed the current temperature control operation, and the current temperature control operation ends;

[0048] When the voltage signal strength measurement result of the dynamic voltage receiving end is not satisfied, the battery pack temperature control operation result data indicates that the battery pack has not completed this temperature control operation, and the next static voltage transmitter specific standard electromagnetic strength interval data in the static voltage transmitter specific standard electromagnetic strength interval data set is selected to re-execute the temperature control operation at the static voltage transmitter of the battery pack.

[0049] A new energy heavy truck logistics intelligent optimization management system, the battery pack includes a battery pack environmental parameter acquisition module, a static battery pack transmitting end voltage signal analysis execution module, and a dynamic battery pack receiving end voltage signal monitoring module.

[0050] Compared with the existing technology, the present invention provides an intelligent optimization management system for new energy heavy-duty truck logistics, which cooperates with the dynamic voltage receiving end voltage strength acquisition unit and the dynamic voltage receiving end voltage signal strength measurement and analysis unit to accurately feedback the voltage strength parameters of the battery pack receiving end through the voltage sensor and scientifically compare it with the receiving end voltage strength threshold, thereby realizing accurate monitoring of the battery pack measurement receiving end voltage strength characteristics and accurate feedback of the battery pack voltage measurement process; the battery pack temperature control operation result judgment processing unit accurately monitors the temperature control operation results of the battery pack temperature control system, thereby improving the temperature control accuracy and operation safety of the battery pack temperature control operation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0052] Figure 1 A schematic diagram of the overall method flow provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0054] See also Figure 1 , a new energy heavy truck logistics intelligent optimization management system, comprising the following steps:

[0055] S1. Collect battery pack ambient temperature data and battery pack ambient electromagnetic intensity data;

[0056] S2. Perform data preprocessing on the battery pack ambient temperature data and the ambient electromagnetic intensity data, and generate standard battery pack ambient temperature data and standard battery pack ambient electromagnetic intensity data;

[0057] S3. Use a data recognition algorithm to analyze and match the standard battery pack ambient temperature data and the standard battery pack ambient electromagnetic intensity data, respectively, to construct and output the specific standard electromagnetic intensity interval data of the static voltage transmitter;

[0058] S4. Execute the operation of transmitting a temperature control signal from the static voltage transmitting end according to the specific standard electromagnetic intensity interval data of the static voltage transmitting end;

[0059] S5. When the static voltage transmitting end transmits a temperature control signal, collecting voltage intensity data of the dynamic voltage receiving end;

[0060] S6. Compare the voltage strength data of the dynamic voltage receiving terminal with the voltage strength threshold data of the dynamic voltage receiving terminal, and analyze and construct a voltage signal strength measurement result of the dynamic voltage receiving terminal based on the voltage strength comparison result of the dynamic voltage receiving terminal;

[0061] S7. Analyze and determine the battery pack temperature control operation result data based on the voltage signal strength measurement result of the dynamic voltage receiving end and process it.

[0062] S1 includes the following steps:

[0063] S11. Collecting the temperature of the environment in which the liquid-cooled power battery pack is located online through a temperature sensor and generating battery pack ambient temperature data, where the battery pack ambient temperature data is in degrees Celsius;

[0064] S12. Collect the electromagnetic intensity of the battery pack's environment online through an electromagnetic intensity measuring instrument and generate battery pack environment electromagnetic intensity data, where the unit of the battery pack environment electromagnetic intensity data is Tesla / meter.

[0065] S2 includes the following steps:

[0066] The adaptive filtering method is used to perform data noise reduction preprocessing on the battery pack ambient temperature data and the battery pack measured ambient electromagnetic intensity data respectively. After the data noise reduction preprocessing, the standard battery pack measured ambient temperature data and the standard battery pack ambient electromagnetic intensity data are generated. The unit of the standard battery pack measured ambient temperature data is Celsius, and the unit of the standard battery pack ambient electromagnetic intensity data is Tesla / meter.

[0067] S3 includes the following steps:

[0068] S31, obtaining standard battery pack ambient temperature data and standard battery pack ambient electromagnetic intensity data;

[0069] S32. Establishing a data set of standard ambient temperature and electromagnetic intensity intervals at the static voltage transmitter

[0070]

[0071] in T n Indicates the standard ambient temperature range of the nth static voltage transmitter. Indicates the maximum value of the standard ambient temperature range of the static voltage transmitter, the standard ambient temperature range of the static voltage transmitter is T1 to The corresponding ambient temperature values ​​increase in sequence; m1=1,2,3,…,θ1

[0072] , represents the m1th static voltage transmitter standard electromagnetic intensity interval data corresponding to the static voltage transmitter standard ambient temperature interval T1, θ1 represents the maximum number of static voltage transmitter standard electromagnetic intensity interval data corresponding to the static voltage transmitter standard ambient temperature interval T1, The unit is Tesla / meter; m n =1,2,3,…,θ n , Indicates the standard ambient temperature range T of the static voltage transmitter n The corresponding mth n The standard electromagnetic intensity interval data of the static voltage transmitting end, θ nIndicates the standard ambient temperature range T of the static voltage transmitter n The maximum value of the corresponding static voltage transmitter standard electromagnetic intensity interval data quantity, The unit is Tesla / meter; Indicates the standard ambient temperature range of the static voltage transmitter The corresponding The standard electromagnetic intensity interval data of the static voltage transmitting end, Indicates the standard ambient temperature range of the static voltage transmitter The maximum value of the corresponding static voltage transmitter standard electromagnetic intensity interval data quantity, The unit is Tesla / meter;

[0073] S33, using a data recognition algorithm to identify the standard battery pack measured ambient temperature data, the standard battery pack ambient electromagnetic intensity data and the static voltage transmitter standard ambient temperature and electromagnetic intensity interval data set of the static voltage transmitter standard ambient temperature interval T n And static voltage transmitter standard electromagnetic intensity interval data The standard electromagnetic intensity interval data of the static voltage transmitter is matched based on the temperature data and electromagnetic intensity data. The standard electromagnetic intensity interval data of the static voltage transmitter matched by the data recognition algorithm Perform matching scoring, which specifically includes the following steps:

[0074] E1, filters out useless features in the finished model vector feature information, uses the sigmoid activation function as the gate state, and then performs a dot product with the finished model vector feature, and then uses the tanh activation function to obtain the gate unit feature screening;

[0075] E2, use the attention mechanism to strengthen the key vector feature information in the electromagnetic intensity interval database, and obtain the embedding vector t and the feature representation of the text according to the vector feature type. Through tT, each feature in the text is scored to perceive the important information in the text, as shown in the following formula:

[0076]

[0077] Where ɑk represents the feature score, m represents the number of features, d represents the dth feature, and tT represents the feature vector parameter;

[0078] E3, the electromagnetic intensity interval database after evaluation can be expressed as H' att , as shown below:

[0079]

[0080] where H′ att =[h′1, h′2, h′3...h′ m ], α=[α1, α2, α3...α m ] is the attention vector, is the vector matrix of the electromagnetic intensity interval database;

[0081] E4, query representation is obtained by the vector feature information fusion module and the characteristic representation H′ of the electromagnetic intensity interval database att =[h′1, h′2, h′3...h′ m ], and then calculate it by the maximum similarity, through and H′ att The score between the queried electromagnetic intensity interval data and the electromagnetic intensity interval database can be calculated, which is the sum of the maximum similarities represented by each finished product model vector queried and each electromagnetic intensity interval data working vector in the electromagnetic intensity interval database, as shown in the following formula:

[0082]

[0083] in Indicates that there are m query results to be matched, H′ att Indicates that the electromagnetic intensity interval database has n features, Indicates the i-th query result to be matched, h′ j represents the jth feature in the electromagnetic intensity interval database;

[0084] S34, all the static voltage transmitter standard electromagnetic intensity interval data output from step S33 Identify and generate specific standard electromagnetic intensity interval data of the static voltage transmitting end and establish a specific standard electromagnetic intensity interval data set of the static voltage transmitting end;

[0085] S35. Output the generated static voltage transmitting end specific standard electromagnetic intensity interval data set.

[0086] S4 includes the following steps:

[0087] According to the specific standard electromagnetic intensity interval data of the static voltage transmitting end in the specific standard electromagnetic intensity interval data set, the temperature control signal transmission operation is performed at the static voltage transmitting end of the battery pack in order according to the electromagnetic intensity value.

[0088] S5 includes the following steps:

[0089] When the static voltage transmitting end of the battery pack performs the operation of transmitting the temperature control signal, the voltage of the dynamic receiving end of the battery pack is collected online through the voltage sensor to receive the induced voltage intensity generated by the static voltage transmitting end performing the operation of transmitting the temperature control signal, and the induced voltage intensity is marked to generate the dynamic voltage receiving end voltage intensity data V, where V is in volts.

[0090] S6 includes the following steps:

[0091] S61: Establishing voltage intensity threshold data V at the dynamic voltage receiving end D The voltage strength threshold data of the dynamic voltage receiving terminal indicates the minimum voltage strength data received by the dynamic voltage receiving terminal to meet the normal execution of the battery temperature control operation of the battery pack, V D The unit is volt;

[0092] S62: compare the dynamic voltage receiving end voltage strength data V with the dynamic voltage receiving end voltage strength threshold data V D Performing a voltage strength value comparison of the dynamic voltage receiving end, and analyzing and constructing a voltage signal strength measurement result of the dynamic voltage receiving end based on the voltage strength value comparison result of the dynamic voltage receiving end;

[0093] When V≥V D , indicating that the voltage strength received by the dynamic voltage receiving end meets the requirements for the battery pack to perform temperature control normally, and the output voltage signal strength measurement result of the dynamic voltage receiving end is satisfied;

[0094] When V<V D , indicating that the voltage strength received by the dynamic voltage receiving end does not meet the requirements for the battery pack to perform temperature control operations normally, and the output dynamic voltage receiving end voltage signal strength measurement result is unsatisfactory.

[0095] S7 includes the following steps:

[0096] When the voltage signal strength measurement result of the dynamic voltage receiving end is satisfied, the battery pack temperature control operation result data indicates that the battery pack has completed the current temperature control operation, and the current temperature control operation ends;

[0097] When the voltage signal strength measurement result of the dynamic voltage receiving end is not satisfied, the battery pack temperature control operation result data indicates that the battery pack has not completed this temperature control operation, and the next static voltage transmitter specific standard electromagnetic strength interval data in the static voltage transmitter specific standard electromagnetic strength interval data set is selected to re-execute the temperature control operation at the static voltage transmitter of the battery pack.

[0098] The battery pack ambient temperature data acquisition unit and the battery pack ambient electromagnetic intensity data acquisition unit work together to accurately collect the temperature and interference electromagnetic intensity parameters of the battery pack operating environment in real time using temperature sensors and electromagnetic intensity meters. This provides data support for the subsequent precise adjustment of the electromagnetic intensity emitted by the battery pack static voltage transmitter, thereby improving the battery pack measurement accuracy. The battery pack ambient temperature data preprocessing and output unit uses an adaptive filtering method to reduce the noise of the collected battery pack ambient temperature and interference electromagnetic intensity parameters, thereby improving the reliability of the acquisition of the battery pack ambient temperature and interference electromagnetic intensity parameters. At the same time, the dynamic voltage receiving end voltage intensity acquisition unit and the dynamic voltage receiving end voltage signal strength measurement and analysis unit work together to accurately feedback the voltage intensity parameters of the battery pack receiving end through the voltage sensor and scientifically compare them with the receiving end voltage intensity threshold, thereby accurately monitoring the voltage intensity characteristics of the battery pack measurement receiving end and providing accurate feedback on the battery pack voltage measurement process. The battery pack temperature control operation result judgment and processing unit accurately monitors the temperature control operation results of the battery pack temperature control system, thereby improving the temperature control accuracy and operational safety of the battery pack temperature control operation system.

[0099] A new energy heavy truck logistics intelligent optimization management system, the battery pack includes a battery pack environmental parameter acquisition module, a static battery pack transmitting end voltage signal analysis execution module, and a dynamic battery pack receiving end voltage signal monitoring module.

[0100] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

Claims

1. An intelligent optimization management system for new energy heavy truck logistics, characterized by: The steps include: S1. Collect battery pack ambient temperature data and battery pack ambient electromagnetic intensity data; S2. Perform data preprocessing on the battery pack ambient temperature data and the ambient electromagnetic intensity data, and generate standard battery pack ambient temperature data and standard battery pack ambient electromagnetic intensity data; S3. Use a data recognition algorithm to analyze and match the standard battery pack ambient temperature data and the standard battery pack ambient electromagnetic intensity data, respectively, to construct and output the specific standard electromagnetic intensity interval data of the static voltage transmitter; S4, executing the operation of transmitting a temperature control signal from the static voltage transmitting end according to the specific standard electromagnetic intensity interval data of the static voltage transmitting end; S5. When the static voltage transmitting end transmits a temperature control signal, collecting voltage intensity data of the dynamic voltage receiving end; S6. Comparing the voltage strength data of the dynamic voltage receiving end with the voltage strength threshold data of the dynamic voltage receiving end, and analyzing and constructing a voltage signal strength measurement result of the dynamic voltage receiving end based on the voltage strength comparison result of the dynamic voltage receiving end; S7, analyzing and determining battery pack temperature control operation result data based on the voltage signal strength measurement result of the dynamic voltage receiving terminal and processing the data; Said S1 comprises the following steps: S11. Collecting the temperature of the environment in which the liquid-cooled power battery pack is located online through a temperature sensor and generating battery pack ambient temperature data, where the battery pack ambient temperature data is in degrees Celsius; S12. Collecting the electromagnetic intensity of the battery pack's environment online using an electromagnetic intensity measuring instrument and generating battery pack environment electromagnetic intensity data, where the unit of the battery pack environment electromagnetic intensity data is Tesla / meter; The S2 comprises the following steps: An adaptive filtering method is used to perform data noise reduction preprocessing on the battery pack ambient temperature data and the battery pack measured ambient electromagnetic intensity data, respectively. After the data noise reduction preprocessing, standard battery pack measured ambient temperature data and standard battery pack ambient electromagnetic intensity data are generated. The unit of the standard battery pack measured ambient temperature data is Celsius, and the unit of the standard battery pack ambient electromagnetic intensity data is Tesla / meter.

2. The intelligent optimization management system for logistics of new energy heavy trucks according to claim 1 is characterized in that: The S3 includes the following steps: S31, obtaining the standard battery pack environment temperature data and the standard battery pack environment electromagnetic intensity data; S32. Establishing a data set of standard ambient temperature and electromagnetic intensity intervals at the static voltage transmitter in T n Indicates the standard ambient temperature range of the nth static voltage transmitter. Indicates the maximum value of the standard ambient temperature range of the static voltage transmitter, the standard ambient temperature range of the static voltage transmitter is T1 to The corresponding ambient temperature values ​​increase in sequence; m1=1,2,3,…,θ1, represents the m1th static voltage transmitter standard electromagnetic intensity interval data corresponding to the static voltage transmitter standard ambient temperature interval T1, θ1 represents the maximum number of static voltage transmitter standard electromagnetic intensity interval data corresponding to the static voltage transmitter standard ambient temperature interval T1, The unit is Tesla / meter; m n =1,2,3,…,θ n , Indicates the standard ambient temperature range T of the static voltage transmitter n The corresponding mth n The standard electromagnetic intensity interval data of the static voltage transmitting end, θ n Indicates the standard ambient temperature range T of the static voltage transmitter n The maximum value of the corresponding static voltage transmitter standard electromagnetic intensity interval data quantity, The unit is Tesla / meter; Indicates the standard ambient temperature range of the static voltage transmitter The corresponding The standard electromagnetic intensity interval data of the static voltage transmitting end, Indicates the standard ambient temperature range of the static voltage transmitter The maximum value of the corresponding static voltage transmitter standard electromagnetic intensity interval data quantity, The unit is Tesla / meter; S33, using a data recognition algorithm to identify the standard battery pack measured ambient temperature data, the standard battery pack ambient electromagnetic intensity data and the static voltage transmitter standard ambient temperature and electromagnetic intensity interval data set. n And static voltage transmitter standard electromagnetic intensity interval data The standard electromagnetic intensity interval data of the static voltage transmitter is matched based on the temperature data and electromagnetic intensity data. The standard electromagnetic intensity interval data of the static voltage transmitter matched by the data recognition algorithm Perform matching scoring, which specifically includes the following steps: E1, filters out useless features in the finished model vector feature information, uses the sigmoid activation function as the gate state, and then performs a dot product with the finished model vector feature, and then uses the tanh activation function to obtain the gate unit feature screening; E2, use the attention mechanism to strengthen the key vector feature information in the electromagnetic intensity interval database, and obtain the embedding vector t and the feature representation of the text according to the vector feature type. By t T , score each feature in the text to perceive the important information in the text, as shown in the following formula: Among them ɑ k represents the feature score, m represents the number of features, d represents the dth feature, t T represents the eigenvector parameter; E3, the electromagnetic intensity interval database after evaluation can be expressed as H' att , as shown below: where H′ att =[h′1, h′2, h′3...h′ m ], α=[α1, α2, α3...α m ] is the attention vector, is the vector matrix of the electromagnetic intensity interval database; E4, query representation is obtained by the vector feature information fusion module and the characteristic representation H′ of the electromagnetic intensity interval database att =[h′1, h′2, h′3...h′ m ], and then calculate it by the maximum similarity, through and H′ att The score between the queried electromagnetic intensity interval data and the electromagnetic intensity interval database can be calculated, which is the sum of the maximum similarities represented by each finished product model vector queried and each electromagnetic intensity interval data working vector in the electromagnetic intensity interval database, as shown in the following formula: in Indicates that there are m query results to be matched, H′ att Indicates that the electromagnetic intensity interval database has n features, Indicates the i-th query result to be matched, h′ j represents the jth feature in the electromagnetic intensity interval database; S34, all the static voltage transmitter standard electromagnetic intensity interval data output from step S33 Identify and generate specific standard electromagnetic intensity interval data of the static voltage transmitting end and establish a specific standard electromagnetic intensity interval data set of the static voltage transmitting end; S35. Output the generated specific standard electromagnetic intensity interval data set of the static voltage transmitting end.

3. The intelligent optimization management system for logistics of new energy heavy trucks according to claim 2 is characterized in that: The S4 comprises the following steps: The temperature control signal transmission operation is performed at the static voltage transmitting end of the battery pack in order according to the specific standard electromagnetic intensity interval data of the static voltage transmitting end in the specific standard electromagnetic intensity interval data set according to the magnitude of the electromagnetic intensity values.

4. The intelligent optimization management system for logistics of new energy heavy trucks according to claim 3 is characterized in that: The S5 comprises the following steps: When the static voltage transmitting end of the battery pack performs the operation of transmitting the temperature control signal, the voltage of the dynamic receiving end of the battery pack is collected online through the voltage sensor to receive the induced voltage intensity generated by the static voltage transmitting end performing the operation of transmitting the temperature control signal, and the induced voltage intensity is marked to generate the dynamic voltage receiving end voltage intensity data V, where V is in volts.

5. The intelligent optimization management system for logistics of new energy heavy trucks according to claim 4 is characterized by: The S6 comprises the following steps: S61: Establishing voltage intensity threshold data V at the dynamic voltage receiving end D The voltage strength threshold data of the dynamic voltage receiving terminal indicates the minimum voltage strength data received by the dynamic voltage receiving terminal to meet the normal execution of the battery temperature control operation of the battery pack, V D The unit is volt; S62: compare the dynamic voltage receiving end voltage strength data V with the dynamic voltage receiving end voltage strength threshold data V D Performing a voltage strength value comparison of the dynamic voltage receiving end, and analyzing and constructing a voltage signal strength measurement result of the dynamic voltage receiving end based on the voltage strength value comparison result of the dynamic voltage receiving end; When V≥V D , indicating that the voltage strength received by the dynamic voltage receiving end meets the requirements for the battery pack to perform temperature control normally, and the output voltage signal strength measurement result of the dynamic voltage receiving end is satisfied; When V<V D , indicating that the voltage strength received by the dynamic voltage receiving end does not meet the requirements for the battery pack to perform temperature control operations normally, and the output dynamic voltage receiving end voltage signal strength measurement result is unsatisfactory.

6. The intelligent optimization management system for logistics of new energy heavy trucks according to claim 5 is characterized by: The S7 comprises the following steps: When the voltage signal strength measurement result of the dynamic voltage receiving end is satisfied, the battery pack temperature control operation result data indicates that the battery pack has completed the current temperature control operation, and the current temperature control operation ends; When the voltage signal strength measurement result of the dynamic voltage receiving end is not satisfied, the battery pack temperature control operation result data indicates that the battery pack has not completed this temperature control operation, and the next static voltage transmitter specific standard electromagnetic strength interval data in the static voltage transmitter specific standard electromagnetic strength interval data set is selected to re-execute the temperature control operation at the static voltage transmitter of the battery pack.

7. A battery pack for implementing a new energy heavy truck logistics intelligent optimization management system as described in any one of claims 1 to 6, characterized in that: The battery pack includes a battery pack environmental parameter acquisition module, a static battery pack transmitting end voltage signal analysis execution module, and a dynamic battery pack receiving end voltage signal monitoring module.

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