An energy management method for diesel-electric hybrid systems with wide operating temperature range

Abstract

This invention discloses an energy management method for diesel-electric hybrid systems in a wide-temperature operating environment, relating to the field of diesel-electric hybrid system energy management technology. It solves the problem that existing diesel-electric hybrid system energy management methods cannot meet the stable operation requirements of the system under various environmental conditions. The method includes: conducting experiments on the power battery system under different temperature conditions to obtain the maximum charging and discharging power of the power battery system under each temperature condition; obtaining the abnormal temperature rise rate threshold of the power battery system under different temperature conditions based on historical operating data of the power battery system; obtaining historical typical data on overheating of the power battery system under various typical operating conditions to obtain the reference feature vector of the power battery system under each typical operating condition; performing over-temperature warning judgment based on the real-time operating data of the power battery system; if the over-temperature warning judgment passes, the battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature warning level.

Description

Technical Field

[0001] This invention relates to the field of energy management technology for diesel-electric hybrid systems, and in particular to an energy management method for diesel-electric hybrid systems for wide-temperature operating scenarios. Background Technology

[0002] Traditional power supply platforms for special equipment mainly rely on diesel generators. These generators operate at a wide range of points, and during system design, diesel engines are selected based on their maximum power output to meet power demand. However, in actual operation, the system often operates for extended periods in the low-to-medium load range of the diesel engine, corresponding to many inefficient operating points, resulting in low overall system efficiency. Furthermore, the system exhibits poor dynamic characteristics and limited adaptability to rapidly changing operating conditions.

[0003] With the energy crisis and the growing demand for green and low-carbon technologies, lithium-ion battery technology has developed rapidly, characterized by its excellent transient characteristics and high charge-discharge performance. Power supply platforms are beginning to adopt a hybrid approach combining diesel generators and lithium-ion batteries. This improves the operating point of the diesel generator while fully leveraging the excellent dynamic characteristics and strong instantaneous discharge capability of lithium-ion batteries. This combination can meet the system's demands for both instantaneous high power and long-term system power consumption, while further improving system efficiency and power density.

[0004] For diesel-electric hybrid power systems consisting of a diesel generator and a lithium-ion battery, designing a reasonable energy management strategy to coordinate and control the two energy sources is crucial for the safe, stable, efficient, and reliable operation of the system. Traditional diesel-electric hybrid energy management strategies focus on system efficiency and fuel consumption, using state variables such as the battery's state of charge (SOC) as key parameters in the control strategy design.

[0005] Most diesel-electric hybrid systems require an operating environment temperature of 0-40℃. Battery performance is significantly affected by temperature, and to ensure battery performance and lifespan, it's necessary to control their operation within a reasonable temperature range. Traditional energy management strategies only implement passive system control after detecting a temperature exceeding a safety threshold, with the battery system temperature primarily regulated by the BMS (Battery Management System) through thermal management. In wide-temperature-range (-40℃ to 50℃) applications, traditional energy management control methods are significantly inadequate and struggle to meet the system's stable operation requirements. First, they lack environmental adaptability. Under extreme high-temperature (50℃) and low-temperature (-40℃) conditions, traditional energy management control relies solely on the battery's own thermal management regulation, lacking coordinated optimization control of the entire system. This singular thermal management strategy cannot effectively cope with complex temperature changes, making it difficult for the battery system to maintain within the safe temperature threshold range. Second, they exhibit poor system stability. Under high-temperature conditions, traditional control methods easily cause the power system to exceed safety thresholds, leading to system failure and inability to meet power demands. In low-temperature environments, battery performance is also severely affected, further reducing the overall system performance and reliability. Third, they rely on passive fault response. Traditional energy management and control systems can only passively control systems after a failure, lacking proactive prevention and optimization measures. This makes it difficult for the system to adjust its operating strategy in a timely manner when facing complex operating conditions, thus increasing the probability of failure. Fourth, there are issues with battery life degradation and safety hazards. Because traditional control methods cannot effectively maintain the battery within a safe temperature range, the battery's lifespan will decrease more rapidly. More seriously, under high-temperature environments, the battery may experience thermal runaway and other serious safety problems, posing a threat to system and personnel safety.

[0006] Therefore, it is crucial to optimize and upgrade the energy management strategy of diesel-electric hybrid systems under wide temperature operating scenarios so that the system can operate continuously and stably under various operating conditions. Summary of the Invention

[0007] Based on the above analysis, the present invention aims to provide an energy management method for diesel-electric hybrid systems in a wide-temperature operating environment, in order to solve the problem that the energy management of existing diesel-electric hybrid systems is difficult to meet the stable operation requirements of the system under various environmental conditions.

[0008] This invention discloses an energy management method for a diesel-electric hybrid system for wide-temperature operating scenarios, the method comprising:

[0009] Experiments were conducted on the power battery system under different temperature conditions to obtain the maximum charging and discharging power of the power battery system under each temperature condition;

[0010] Based on the historical operating data of the power battery system, obtain the threshold of abnormal temperature rise rate of the power battery system under different temperature conditions.

[0011] Obtain historical typical data on overheating of the power battery system under various typical operating conditions, and obtain reference feature vectors of the power battery system under various typical operating conditions.

[0012] Over-temperature warnings are detected based on real-time operating data of the power battery system. If the over-temperature warning is detected, the battery energy management system will actively adjust the energy management strategy of the power battery system according to the over-temperature warning level.

[0013] Based on the above solution, the present invention also makes the following improvements:

[0014] Furthermore, the over-temperature warning judgment based on the real-time operating data of the power battery system includes determining whether the real-time operating data meets the power judgment condition, the heating rate judgment condition, and the feature vector judgment condition. If the real-time operating data meets at least one judgment condition, the over-temperature warning judgment passes, and the number of judgment conditions met is used as the over-temperature warning level. Otherwise, the over-temperature warning judgment fails, and the battery energy management system controls the power battery system according to the conventional strategy.

[0015] Furthermore, the step of determining whether the real-time operating data meets the power discrimination condition involves: obtaining the temperature conditions matching the real-time temperature inside the battery box, and determining whether the real-time battery power is greater than the maximum discharge power under the current temperature conditions, or less than the maximum charging power under the current temperature conditions.

[0016] If so, then the power discrimination condition is met;

[0017] Otherwise, it is not satisfied.

[0018] Furthermore, the step of determining whether the real-time operating data meets the temperature rise rate discrimination condition involves: obtaining the temperature conditions matching the real-time temperature inside the battery box; calculating the real-time temperature rise rate based on the highest real-time temperature of each battery cell; and determining whether the real-time temperature rise rate exceeds the abnormal temperature rise rate threshold under the current temperature conditions.

[0019] If so, then the heating rate discrimination condition is met;

[0020] Otherwise, it is not satisfied.

[0021] Furthermore, the step of determining whether the real-time operating data meets the feature vector discrimination condition involves: determining whether the real-time battery box temperature belongs to typical operating conditions.

[0022] If it does not belong to, then the eigenvector discrimination condition is not met;

[0023] Otherwise, obtain typical operating conditions for real-time temperature matching within the battery box, and construct corresponding real-time feature vectors based on the real-time load power, real-time maximum temperature of individual battery cells, real-time minimum temperature of individual battery cells, and the maximum value of the real-time temperature difference between individual battery cells. Calculate the Euclidean distance between the real-time feature vectors and the reference feature vectors under the current typical operating conditions.

[0024] If it is less than the distance threshold, then the feature vector discrimination condition is met;

[0025] Otherwise, it is not satisfied.

[0026] Furthermore, the battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature warning level, and executes the following:

[0027] In response to the Level 1 warning, the discharge power of the power battery system is reduced to 70% of the rated value to supply power to the load, and the remaining power required for the load operation is supplemented by the diesel generator.

[0028] For Level 2 warning, the discharge power of the power battery system is reduced to 50% of the rated value to supply power to the load, the diesel generator is used to supplement the remaining power required for the load to operate, and the cooling system is controlled to operate at full power.

[0029] For the three-level warning, the discharge power of the power battery system is reduced to 30% of the rated value to supply power to the load, the diesel generator is used to supplement the remaining power required for the load to operate, and the cooling system is controlled to operate at full power; if the diesel generator cannot supplement the remaining power required for the load to operate, the power supply priority of the electrical load is adjusted in stages.

[0030] Furthermore, the battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature warning level, and also performs the following:

[0031] When the over-temperature warning level is detected to be decreasing step by step, and after the low level continues for a certain period of time, the energy management strategy is updated according to the reduced over-temperature warning level; until the over-temperature warning continues for the specified period of time and the judgment fails, the battery energy management system resumes the normal strategy to control the power battery system.

[0032] Furthermore, the maximum charge and discharge power of the power battery system under various temperature conditions is obtained by performing the following operations:

[0033] The power battery system is placed in a temperature chamber, and the temperature range of the temperature chamber is set according to the wide temperature usage scenario. Based on the temperature adjustment accuracy of the temperature chamber, multiple different temperature conditions are formed within the temperature range of the temperature chamber.

[0034] Under each temperature condition, the heat dissipation system is controlled to operate at maximum cooling power; different load powers are applied to the power battery system, and the charging and discharging power of the power battery system under each load power is monitored to obtain the maximum charging and discharging power of the power battery system under the corresponding temperature conditions.

[0035] Furthermore, the historical operating data of the power battery system includes: the temperature inside the battery box, and the curve of the highest temperature of the battery cells changing over time.

[0036] Furthermore, the abnormal temperature rise rate threshold of the power battery system under different temperature conditions is obtained by performing the following operations:

[0037] Based on the temperature variation range inside the battery box, different temperature conditions are divided; multiple curves of the maximum temperature of each battery cell as a function of temperature are obtained under each temperature condition.

[0038] Under each temperature condition, the curve that satisfies the condition of an upward trend and the maximum value of the highest temperature of the battery cell in the curve is greater than the abnormal temperature threshold of the corresponding temperature condition is designated as an abnormal curve; based on each abnormal curve, the abnormal temperature rise rate threshold of the power battery system under the corresponding temperature condition is determined.

[0039] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0040] This invention provides an energy management method for diesel-electric hybrid systems operating in a wide temperature range. Based on information such as battery temperature, heating rate, and load power, the method predicts battery temperature trends and proactively adjusts the power distribution between the two energy sources at the system level. It actively controls the operating level of the cooling system within the battery thermal management system, and classifies the importance of loads under extreme conditions, proactively controlling the power distribution or consumption of each load to ensure the battery system temperature remains within a safe and reasonable range. This method effectively improves the safe, stable, efficient, and reliable operation of diesel-electric hybrid systems under various environmental conditions in wide temperature ranges, ensuring the system successfully completes its power supply tasks.

[0041] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0042] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0043] Figure 1 A flowchart illustrating an energy management method for a diesel-electric hybrid system for wide-temperature operating scenarios, provided in an embodiment of the present invention. Detailed Implementation

[0044] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0045] In a diesel-electric hybrid system, the power battery system and the cooling system cooperate and constrain each other to ensure the normal operation and performance of the entire system. Specifically, the power battery system is one of the core components of the diesel-electric hybrid system, providing energy for the vehicle's electric drive. The main function of the cooling system is to ensure the power battery system can operate normally in high-temperature environments. Its functions include: 1) Conventional cooling: During normal vehicle operation, the power battery is cooled using the conventional power setting to ensure the battery temperature remains within a safe range; 2) High-power cooling: When the vehicle is under high load or the battery temperature is too high, the system switches to a high-power setting to quickly reduce the battery temperature and prevent overheating damage. Through precise temperature management and reasonable energy distribution, the diesel-electric hybrid system can operate efficiently and safely under various environmental conditions.

[0046] A specific embodiment of the present invention discloses an energy management method for a diesel-electric hybrid system for wide-temperature operating scenarios, the flowchart of which is shown below. Figure 1 As shown, the specific implementation process is described below.

[0047] Step S1: Conduct experiments on the power battery system under different temperature conditions to obtain the maximum charging and discharging power of the power battery system under each temperature condition.

[0048] Step S11: Place the power battery system in the temperature chamber and set the temperature range of the temperature chamber according to the wide temperature usage scenario; based on the temperature adjustment accuracy of the temperature chamber, create multiple different temperature conditions within the temperature range of the temperature chamber.

[0049] For example, since the wide-temperature operating scenario in this embodiment is -40℃ to 50℃, the temperature range of the temperature chamber can also be set to -40℃ to 50℃. Assuming the temperature adjustment accuracy of the temperature chamber is 0.5℃, multiple different temperature conditions are formed within the temperature range of the temperature chamber with a temperature interval of 0.5℃ to simulate the operating environment temperature of the power battery system under wide-temperature operating scenarios, thereby realizing the experiment of the power battery system under different temperature conditions.

[0050] Step S12: Under each temperature condition, control the heat dissipation system to operate at the maximum cooling power; apply different load powers to the power battery system, monitor the charging and discharging power of the power battery system under each load power, and obtain the maximum charging and discharging power of the power battery system under the corresponding temperature conditions.

[0051] During the experiment, the cooling system always operated at maximum cooling power to ensure that the power battery system could fully utilize its heat dissipation capacity, thereby accurately reflecting the performance of the power battery system under the limitation of heat dissipation capacity.

[0052] By adjusting the load power, the power battery system is operated at different power levels. Under each temperature condition, different load powers are sequentially applied to the power battery system, and the charging and discharging power of the power battery system is monitored in real time. Preferably, the HPPC (Hybrid Pulse Power Characterization) method is a widely used general method for battery testing, which can effectively evaluate the battery performance under different charging and discharging powers. Therefore, in this embodiment, the HPPC method can be used to test the power battery system to monitor its charging and discharging power in real time.

[0053] Under the set temperature conditions, by iterating through the charging and discharging power of the power battery system under different load power, the maximum charging and discharging power of the power battery system under the corresponding temperature conditions can be obtained. Repeating step S12, the maximum charging and discharging power of the power battery system under various temperature conditions can be obtained, providing sufficient basis for the performance evaluation of the power battery system under different temperature environments.

[0054] Step S2: Based on the historical operating data of the power battery system, obtain the threshold of abnormal temperature rise rate of the power battery system under different temperature conditions.

[0055] Preferably, in this embodiment, the historical operating data of the power battery system includes: the temperature inside the battery box (i.e., the ambient temperature of the power battery system) and the curve of the highest temperature of the battery cell changing over time.

[0056] Step S21: Divide the operating conditions into different temperature ranges according to the temperature variation range inside the battery box; obtain the curves of the maximum temperature of multiple battery cells as a function of temperature under each temperature condition.

[0057] Step S22: Under each temperature condition, the curve that satisfies the condition of an upward trend and the maximum value of the highest temperature of the battery cell in the curve is greater than the abnormal temperature threshold of the corresponding temperature condition is taken as an abnormal curve; based on each abnormal curve, the abnormal temperature rise rate threshold of the power battery system under the corresponding temperature condition is determined.

[0058] In the specific implementation process, in step S21, since the wide-temperature operating scenario in this embodiment is -40℃ to 50℃, and the higher the temperature, the more sensitive it is to abnormal temperature rise, different temperature conditions can be divided in this embodiment as follows: When the temperature inside the battery box is between -40℃ and 40℃, different temperature conditions are divided in 5℃ increments. The divided temperature conditions are such as (-40°, -35°], (-35°, -30°], etc. When the temperature inside the battery box is between 40℃ and 50°, different temperature conditions are divided in 2° increments, such as (40°, 42°], (42°, 44°], etc.

[0059] In step S22, the curve that satisfies the conditions of an upward trend and a maximum maximum temperature of the battery cell exceeding the abnormal temperature threshold for the corresponding temperature condition is designated as an abnormal curve. An upward trend indicates that the maximum temperature of the battery cell is continuously increasing; a maximum maximum temperature exceeding the abnormal temperature threshold indicates that the maximum temperature of the battery cell exceeds the upper limit of normal temperature rise for the current operating condition. In practice, the upper limit temperature of the operating condition plus 5°C can be used as the abnormal temperature threshold for the corresponding temperature condition.

[0060] After obtaining multiple abnormal curves (the maximum temperature of a single battery cell varies with temperature), the abnormal temperature rise rate for each time period can be calculated based on the abnormal curves, and the maximum value of the abnormal temperature rise rate for the corresponding abnormal curve can be obtained. The average value of the maximum abnormal temperature rise rate of all abnormal curves is calculated, and the average value or a preset percentage of the average value (e.g., 80% of the average value) is used as the abnormal temperature rise rate threshold of the power battery system under the corresponding temperature conditions.

[0061] Step S3: Obtain historical typical data on overheating of the power battery system under various typical operating conditions, and obtain the reference feature vector of the power battery system under various typical operating conditions.

[0062] In the wide-temperature operating scenario provided in this embodiment, overheating of the power battery system is only possible when the temperature inside the battery pack reaches a certain value. Therefore, in this embodiment, 35°-50°C is selected as the typical overheating scenario, and with a temperature change of 5°C, three typical operating conditions are obtained: (35°C, -40°C), (40°C, 45°C), and (45°C, 50°C). Under each typical operating condition, the overheating of the power battery system is manifested by the highest temperature of a single battery cell exceeding 50°C.

[0063] In this embodiment, multiple sets of historical typical data under various typical operating conditions are obtained. Each set of historical typical data includes: the maximum value of load power, the highest temperature of a single battery cell, the lowest temperature of a single battery cell, and the maximum value of the temperature difference between single battery cells.

[0064] In the specific implementation process, under each typical working condition, a corresponding feature vector is constructed based on each set of historical typical data. The cluster center of the feature vectors of each set of historical typical data is used as the reference feature vector of the power battery system under the corresponding typical working condition.

[0065] Step S4: Based on the real-time operating data of the power battery system, an over-temperature warning is determined. If the over-temperature warning is determined, the battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature warning level.

[0066] Step S41: Obtain real-time operating data of the power battery system, including: real-time battery box temperature, real-time battery power, real-time load power, real-time maximum temperature of individual battery cells, real-time minimum temperature of individual battery cells, and the maximum value of the real-time temperature difference between individual battery cells.

[0067] Step S42: Perform over-temperature warning judgment based on the real-time operating data of the power battery system, including judging whether the real-time operating data meets the power judgment condition, the heating rate judgment condition, and the feature vector judgment condition; if the real-time operating data meets at least one judgment condition, the over-temperature warning judgment passes, and the number of judgment conditions met is used as the over-temperature warning level.

[0068] (1) Power discrimination condition

[0069] The power discrimination condition matches step S1. Specifically, to determine whether the real-time operating data meets the power discrimination condition, the following steps are performed: obtain the temperature conditions matching the real-time battery box temperature, and determine whether the real-time battery power is greater than the maximum discharge power (discharge is positive) under the current temperature conditions, or less than the maximum charging power (charging) under the current temperature conditions.

[0070] If so, then the power discrimination condition is met;

[0071] Otherwise, it is not satisfied.

[0072] (2) Conditions for determining the rate of heating

[0073] The temperature rise rate discrimination condition matches step S2. Specifically, to determine whether the real-time operating data meets the temperature rise rate discrimination condition, the following steps are performed: obtain the temperature conditions matching the real-time temperature inside the battery box; calculate the real-time temperature rise rate based on the highest real-time temperature of each battery cell; and determine whether the real-time temperature rise rate exceeds the abnormal temperature rise rate threshold under the current temperature conditions.

[0074] If so, then the heating rate discrimination condition is met;

[0075] Otherwise, it is not satisfied.

[0076] (3) Eigenvector discrimination conditions

[0077] The feature vector discrimination condition matches step S3. Specifically, to determine whether the real-time operating data meets the feature vector discrimination condition, the following steps are performed: Determine whether the real-time battery box temperature belongs to a typical operating condition. If not, the feature vector discrimination condition is not met; otherwise, obtain the typical operating condition matching the real-time battery box temperature, and construct the corresponding real-time feature vector based on the real-time load power, the real-time maximum temperature of the battery cell, the real-time minimum temperature of the battery cell, and the maximum value of the real-time temperature difference between the battery cells. Calculate the Euclidean distance between the real-time feature vector and the reference feature vector under the current typical operating condition. If the distance is less than the distance threshold, the feature vector discrimination condition is met; otherwise, it is not met.

[0078] If the overheating warning is approved, the number of conditions met will be used as the overheating warning level. That is, if one condition is met, the overheating warning level is Level 1; if two conditions are met, the overheating warning level is Level 2; and if three conditions are met, the overheating warning level is Level 3.

[0079] Step S43: The battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature warning level.

[0080] (1) For Level 1 warning, the energy management strategy is to control the discharge power of the power battery system to be reduced to 70% of the rated value to supply power to the load, and control the diesel generator to supplement the remaining power required for the load operation (total system load power - battery power).

[0081] (2) For Level II warning, the energy management strategy is to control the discharge power of the power battery system to be reduced to 50% of the rated value to supply power to the load, control the diesel generator to supplement the remaining power required for the load operation, and control the cooling system to operate at full power.

[0082] (3) For the three-level warning, the energy management strategy is as follows: control the discharge power of the power battery system to be reduced to 30% of the rated value to supply power to the load, control the diesel generator to supplement the remaining power required for the load to run, and control the cooling system to run at full power; if the diesel generator cannot supplement the remaining power required for the load to run (at this time the available power in the system cannot meet the full operation of the load), then the power supply priority of the electrical load is used for graded regulation.

[0083] Specifically, the power supply priority of electrical loads is sorted according to their importance, and the power distribution of loads with lower priority is stopped or the power is limited until the remaining load power is less than or equal to the available power of the system.

[0084] Step S44: When the over-temperature warning level is detected to be decreasing step by step, and after the low level continues for a certain period of time (5 minutes), the energy management strategy is updated according to the reduced over-temperature warning level; until the over-temperature warning continues for the specified period of time and the judgment fails, the battery energy management system resumes the normal strategy to control the power battery system.

[0085] That is, the over-temperature warning mode is exited. For example, when it is detected that the system over-temperature warning level is decreasing step by step and remains at a low level for 5 minutes, the load power supply is restored sequentially according to the strategy in step S43, and the output ratio of the power battery is restored. When the over-temperature warning level disappears (that is, the three discrimination conditions in step S42 do not occur for 5 minutes and are judged as the warning level disappearing), the energy management system continues to control according to the normal strategy.

[0086] In summary, the energy management method for diesel-electric hybrid systems with wide operating temperature range provided in this embodiment has the following advantages.

[0087] (1) Improve system security

[0088] 1) Precise Over-Temperature Warning: By combining three criteria—power discrimination, heating rate discrimination, and feature vector discrimination—the system provides comprehensive and accurate warnings about over-temperature conditions in the power battery system. Under different temperature conditions and operating states, it can promptly and accurately detect abnormal situations that may lead to overheating, effectively preventing safety accidents caused by over-temperature, such as battery thermal runaway, and ensuring the safe operation of the entire diesel-electric hybrid system.

[0089] 2) Tiered Control Strategy: Based on different over-temperature warning levels, corresponding energy management strategies are adopted. As the warning level increases, the discharge power of the power battery system is gradually reduced, and the diesel generator supplements the power. Simultaneously, at level three warning, the cooling system is controlled to operate at full power, and even the electrical load is subject to tiered control. This tiered control method can rationally adjust the system's operating state according to different degrees of over-temperature severity, minimizing the threat posed by over-temperature to system safety and ensuring safe and stable operation of the system under various complex operating conditions.

[0090] (2) Optimize energy management

[0091] 1) Adaptable to Wide Temperature Range: This invention is designed for wide temperature range applications, fully considering the performance differences of the power battery system under different temperature conditions. Through experiments at various temperatures, the maximum charge and discharge power of the power battery system under each temperature condition is obtained, and the threshold for abnormal temperature rise rate is determined based on historical operating data. This enables the energy management system to rationally allocate and manage energy according to the actual performance characteristics under different temperature conditions, optimizing the energy utilization efficiency of the entire diesel-electric hybrid system over a wide temperature range and improving the system's adaptability and stability under different ambient temperatures.

[0092] 2) Improve energy utilization efficiency: After the over-temperature warning is passed, the energy management strategy of the power battery system is actively adjusted according to the warning level. For example, in the case of a level one warning, the discharge power of the power battery system is reduced to 70% of the rated value, and the remaining power is supplemented by the diesel generator. This not only avoids the performance degradation or damage caused by the over-discharge of the power battery system due to over-temperature, but also makes full use of the power output of the diesel generator to ensure the normal operation of the system load. This achieves reasonable energy allocation and efficient utilization, and improves the energy utilization efficiency of the entire system.

[0093] (3) Enhance system reliability

[0094] 1) Decision-making based on historical and experimental data: When determining key parameters such as the abnormal temperature rise rate threshold and reference eigenvector, not only historical operating data of the power battery system is considered, but also experimental data under different temperature conditions are incorporated. This decision-making approach based on a large amount of real-world data makes the formulation of energy management strategies more scientific and reasonable, better reflecting the performance characteristics and abnormal situations of the power battery system in actual operation, thereby improving the system's adaptability and reliability to various complex operating conditions.

[0095] 2) Load tiered control ensures the supply of critical loads: In the event of a Level 3 warning, if the diesel generator is unable to replenish the remaining power required for the load operation, tiered control will be implemented according to the power supply priority of the electrical loads, prioritizing the power supply to critical loads. This tiered control mechanism ensures that critical equipment and important functions can still operate normally when the system power is insufficient, enhancing the reliability and stability of the system under extreme conditions and reducing the risk of overall system failure due to overheating.

[0096] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0097] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for energy management of a diesel-electric hybrid system for wide temperature use scenarios, characterized in that, The method comprises: respectively under different temperature conditions on the power battery system experiment, get power battery system under each temperature condition of the maximum charge, discharge power; According to the historical operation data of the power battery system, the abnormal temperature rising rate threshold of the power battery system under different temperature conditions is obtained; Get the history typical data of the power battery system under each typical condition, get the reference feature vector of the power battery system under each typical condition; According to the real-time operation data of the power battery system, the over-temperature early warning discrimination is carried out, if the over-temperature early warning discrimination is passed, the battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature early warning level; The over-temperature early warning discrimination according to the real-time operation data of the power battery system comprises judging whether the real-time operation data meets the power discrimination condition, the temperature rising rate discrimination condition and the feature vector discrimination condition; wherein the power discrimination condition is obtained based on the maximum charge and discharge power under each temperature condition, the temperature rising rate discrimination condition is obtained based on the abnormal temperature rising rate threshold under different temperature conditions, and the feature vector discrimination condition is obtained based on the reference feature vector under each typical condition; if the real-time operation data at least meets one discrimination condition, the over-temperature early warning discrimination is passed, and the number of the met discrimination conditions is taken as the over-temperature early warning level; otherwise, the over-temperature early warning discrimination is not passed, and the battery energy management system controls the power battery system according to the conventional strategy.

2. The method according to claim 1, wherein, The judgment whether the real-time operation data meets the power discrimination condition is executed: the temperature condition matched with the real-time battery box temperature is obtained, it is judged whether the real-time battery power is greater than the maximum discharge power under the current temperature condition or less than the maximum charge power under the current temperature condition, If yes, the power discrimination condition is met; Otherwise, it is not met.

3. The method according to claim 2, wherein, The judgment whether the real-time operation data meets the temperature rising rate discrimination condition is executed: the temperature condition matched with the real-time battery box temperature is obtained, the real-time temperature rising rate is calculated according to the real-time battery monomer highest temperature, it is judged whether the real-time temperature rising rate is greater than the abnormal temperature rising rate threshold under the current temperature condition, If yes, the temperature rising rate discrimination condition is met; Otherwise, it is not met.

4. The method according to claim 3, wherein, The judgment whether the real-time operation data meets the feature vector discrimination condition is executed: it is judged whether the real-time battery box temperature belongs to the typical condition, If not, the feature vector discrimination condition is not met; Otherwise, the typical condition matched with the real-time battery box temperature is obtained, and the corresponding real-time feature vector is constructed according to the real-time load power, the real-time battery monomer highest temperature, the real-time battery monomer lowest temperature and the maximum value of the real-time battery monomer temperature difference, the Euclidean distance between the real-time feature vector and the reference feature vector under the current typical condition is calculated, If less than the distance threshold, the feature vector discrimination condition is met; Otherwise, it is not met.

5. The energy management method for diesel-electric hybrid system for wide temperature use scenarios according to any one of claims 1-4, characterized in that, The battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature early warning level, which executes: For the first level of early warning, the discharge power of the power battery system is controlled to reduce to 70% of the rated value to supply power for the load, and the remaining power required for the load operation is supplemented by the diesel generator. For the second level of early warning, the discharge power of the power battery system is reduced to 50% of the rated value to supply power to the load, the remaining power required for the load operation is supplemented by the diesel generator, and the heat dissipation system is controlled to operate at full power; For the third level of early warning, the discharge power of the power battery system is reduced to 30% of the rated value to supply power to the load, the remaining power required for the load operation is supplemented by the diesel generator, and the heat dissipation system is controlled to operate at full power; if the diesel generator cannot supplement the remaining power required for the load operation, the power supply priority of the electrical load is classified and controlled.

6. The method according to claim 5, wherein, The battery energy management system actively adjusts the energy management strategy of the power battery system according to the over-temperature early warning level, and also performs: When the over-temperature early warning level is gradually reduced and continues for a certain time length at a low level, the energy management strategy is updated according to the reduced over-temperature early warning level; until the over-temperature early warning continues for the certain time length and fails to pass the test, the battery energy management system restores the normal strategy to control the power battery system.

7. The method according to claim 6, wherein, The maximum charge and discharge power of the power battery system under each temperature condition is obtained by performing the following operations: Place the power battery system in a temperature chamber, set the temperature range of the temperature chamber according to the wide-temperature use scenario, and form multiple different temperature conditions within the temperature range of the temperature chamber according to the temperature adjustment accuracy of the temperature chamber; Under each temperature condition, control the heat dissipation system to operate at the maximum cooling power; apply different load powers to the power battery system, monitor the charge and discharge power of the power battery system under each load power, and obtain the maximum charge and discharge power of the power battery system under the corresponding temperature condition.

8. The method for energy management of diesel-electric hybrid system for wide temperature use scenarios as claimed in claim 3 wherein, The historical operation data of the power battery system includes: the temperature in the battery box, and the curve of the maximum temperature of the battery monomer changing with time.

9. The method according to claim 8, wherein, The abnormal temperature rise rate threshold of the power battery system under different temperature conditions is obtained by performing the following operations: According to the change interval of the temperature in the battery box, different temperature conditions are divided; multiple curves of the maximum temperature of the battery monomer changing with temperature under each temperature condition are obtained; Under each temperature condition, the curve that meets the conditions of upward trend and maximum value of the maximum temperature of the battery monomer in the curve being greater than the abnormal temperature threshold of the corresponding temperature condition is taken as an abnormal curve; according to each abnormal curve, the abnormal temperature rise rate threshold of the power battery system under the corresponding temperature condition is determined.

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