A thermal management system capable of regulating the temperature inside a split battery cabinet

Abstract

The present invention belongs to the technical field of battery cabinets, and specifically relates to a thermal management system capable of regulating the temperature inside a split battery cabinet. By introducing a dynamic adjustment device and a closed-loop feedback mechanism, precise control of the temperature inside the battery cabinet is achieved; the sensing unit monitors environmental changes in real time and quickly starts the heating operation; the dynamic adjustment device automatically optimizes heat distribution based on the actual temperature differences at different locations in the battery cabinet to ensure uniform heat distribution; the feedback monitoring station forms a closed loop with the initial sensing unit, continuously monitoring and adjusting the heating intensity in a timely manner to ensure stable operation and efficient management of the system, significantly improving the effectiveness and reliability of temperature management in the battery cabinet under extremely low temperature conditions, ensuring the optimal working state of the battery and extending its service life.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery cabinets, and in particular relates to a thermal management system capable of regulating the temperature in a split battery cabinet. Background Art

[0002] Existing split-type battery cabinet temperature management systems typically employ fixed heating and cooling strategies to maintain the battery's operating temperature. These systems typically include one or more temperature sensors to monitor ambient and internal temperatures and trigger heating or cooling devices based on preset thresholds. However, this traditional temperature management approach has limitations. Particularly in extremely low-temperature environments, the heating efficiency of existing systems may not be sufficient to quickly and effectively raise the temperature within the battery cabinet to a suitable operating range. Furthermore, fixed heating strategies cannot precisely adjust to specific temperature differences within the battery cabinet, potentially leading to uneven heat distribution and impacting battery performance and lifespan.

[0003] Specifically, the main problem facing existing technologies is that, in extremely low-temperature environments, existing thermal management systems struggle to effectively and evenly heat the entire battery cabinet to maintain the required operating temperature for the batteries. This not only affects the battery's charging and discharging efficiency but can also lead to performance degradation or even damage. Summary of the Invention

[0004] The purpose of the present invention is to provide a thermal management system capable of regulating the temperature inside a split battery cabinet. By introducing a dynamic adjustment device and a closed-loop feedback mechanism, precise control of the temperature inside the battery cabinet is achieved to solve the problems in the prior art raised in the above background technology.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a thermal management system capable of regulating the temperature inside a split battery cabinet, comprising:

[0006] a sensing unit activated in response to changes in environmental conditions, the sensing unit being connected to an analysis and processing center which evaluates whether activation of a heating operation is necessary based on data provided by the sensing unit;

[0007] The analysis and processing center is coupled to a command generator. When it is determined that heating is required, the command generator sends an activation signal to a distributed array of heating elements. After receiving the signal from the command generator, each member of the heating element array triggers an energy conversion component connected thereto to convert electrical energy into thermal energy.

[0008] The energy conversion assembly is connected to a heat conduction network, which is connected to a dynamic adjustment device that automatically optimizes heat distribution based on temperature differences within the battery cabinet;

[0009] The dynamic adjustment device also interacts with a feedback monitoring station to continuously monitor the temperature and adjust the heating intensity in a timely manner. The feedback monitoring station forms a closed loop with the initial sensing unit to ensure the stable operation and management of the entire system.

[0010] Preferably, the sensing unit comprises:

[0011] Environmental parameter detector, used to obtain the ambient temperature T_env;

[0012] a comparison component, configured to receive a temperature value T_env from an environmental parameter detector and compare it with a preset low temperature threshold T_min, and generate an activation signal S_act if T_env is less than T_min;

[0013] The time delay controller, after receiving the activation signal S_act from the comparison component, delays the output of the control signal C_ctrl to the subsequent module according to the preset time interval Δt;

[0014] After receiving the control signal C_ctrl from the time delay controller, the intensity regulator calculates the heating power P_heat that needs to be provided through the formula P_heat=α*(T_target-T_env), where α is the proportional coefficient and T_target is the target maintenance temperature.

[0015] Preferably, the analysis and processing center comprises:

[0016] A data receiving interface, used to receive data D_sense from the sensing unit, including but not limited to the ambient temperature T_env and the temperature inside the battery cabinet T_cab;

[0017] a difference calculation unit connected to the data receiving interface, configured to calculate a difference ΔT_low between T_env and a preset lower operating temperature limit T_min, and a difference ΔT_high between T_cab and a preset upper operating temperature limit T_max, wherein the calculation formulas are ΔT_low=T_min-T_env and ΔT_high=T_cab-T_max;

[0018] A decision logic module receives the ΔT_low and ΔT_high values ​​from the difference calculation unit, and generates a heating request signal R_heat when ΔT_low>0 or ΔT_high<0;

[0019] The priority judge receives the heating request signal R_heat from the decision logic module and checks whether there are other operation instructions O_opr. If there are no other operation instructions with higher priority, the heating request is allowed to pass and a confirmation signal A_conf is sent to the instruction generator.

[0020] Preferably, the instruction generator includes:

[0021] A signal preparation unit, configured to receive a confirmation signal A_conf from the analysis and processing center and prepare an activation command C_cmd according to the signal;

[0022] An address distributor, connected to the signal preparation unit, for distributing a unique address identifier ID_addr to each distributed heating element;

[0023] The power setting module is connected to the address distributor and calculates the required heating power P_set according to the preset heating mode M_heat and the current ambient temperature T_env. The calculation formula is P_set=β*(T_target-T_env), where β is the proportional coefficient;

[0024] The command transmitter receives the P_set value from the power setting module and the ID_addr information from the address distributor, combines them into a complete activation signal S_actv, and sends S_actv to the corresponding heating element.

[0025] Preferably, the heating element array comprises:

[0026] A signal receiving port is used to receive an activation signal S_actv from the instruction generator, where the signal includes an address identifier ID_addr for a specific heating element and a set heating power P_set;

[0027] Verification module, connected to the signal receiving port, verifies whether the ID_addr in the received S_actv matches its own address;

[0028] The current regulation unit receives the activation signal S_actv confirmed by the verification module and adjusts the current I_adj supplied to the energy conversion component according to the value P_set therein. The current adjustment formula is I_adj=P_set / V_supply, where V_supply is the supply voltage;

[0029] The energy conversion component is connected to the current regulation unit, receives the adjusted current I_adj, and converts it into heat energy Q_heat. The conversion relationship follows Joule's law and the calculation formula is Q_heat= *R_heater*t, where R_heater is the heating resistance and t is the time.

[0030] Preferably, the energy conversion component comprises:

[0031] An electric energy receiving interface, configured to receive the adjusted current I_adj from the current regulating unit;

[0032] The resistance heating element is connected to the power receiving interface and converts the received current I_adj into heat energy Q_heat through the internal resistor R_heater. The conversion formula is Q_heat= *R_heater;

[0033] The heat transfer interface is connected to the resistance heating element and is responsible for efficiently transferring the generated heat energy Q_heat to the heat conduction network. The transfer efficiency η_trans is calculated as η_trans=Q_delivered / Q_heat, where Q_delivered is the actual heat transferred to the heat conduction network.

[0034] The temperature monitor is connected to the heat transfer interface to monitor the temperature change T_change during the transfer process in real time, and adjust the working state of the resistance heating element according to the temperature feedback. The adjustment formula is R_heater_adjusted=R_heater*(1+μ*T_change), where μ is the temperature sensitivity coefficient.

[0035] Preferably, the heat conduction network comprises:

[0036] The heat receiving interface is used to directly receive the heat energy Q_heat generated by the energy conversion component and initially homogenize it;

[0037] The thermal medium distributor is connected to the heat receiving interface and transfers heat energy through different paths based on the internal structure of the battery cabinet and the preset heat distribution mode D_mode. The distributor ensures that the heat flow F_path on each path matches the requirements of the required location. The calculation formula is F_path = Q_heat / N_paths, where N_paths is the number of heat conduction paths.

[0038] The multi-layer heat conducting plate receives the heat flow F_path from the heat conducting medium distributor. The multi-layer heat conducting plate is composed of several layers of high-efficiency heat conducting materials. There is optimized contact between each layer to minimize the thermal resistance R_contact. The thermal resistance is calculated as R_contact=δ / (k*A), where δ is the contact thickness between the layers, k is the thermal conductivity, and A is the contact area.

[0039] The temperature balance controller is connected to the multi-layer heat transfer plate to monitor and adjust the temperature difference ΔT_layer between each layer. The controller adjusts the working state of the heat transfer plate according to the real-time temperature feedback so that ΔT_layer ≤ T_tolerance, where T_tolerance is the set temperature tolerance.

[0040] Preferably, the dynamic adjustment device comprises:

[0041] The temperature difference detector is used to monitor the temperature T_pos at different locations in the battery cabinet in real time and calculate the temperature difference ΔT_pos between each location. The calculation formula is ΔT_pos = |T_pos(i) - T_pos_avg|, where T_pos(i) is the actual temperature at a certain location and T_pos_avg is the average temperature of all locations.

[0042] A heat demand estimator is connected to the temperature difference detector and estimates the additional heat required for each position Q_add based on ΔT_pos. The evaluation formula is Q_add(i)=γ*ΔT_pos(i), where γ is the heat compensation coefficient;

[0043] The allocation optimization controller receives the Q_add data from the heat demand estimator and optimizes the heat flow F_opt on each heat conduction path according to the current heat distribution. The optimization formula is F_opt(path)=F_path+Q_add(i) / N_paths_connected, where N_paths_connected is the number of heat conduction paths connected to the location.

[0044] The feedback regulation unit is connected to the distribution optimization controller, continuously monitors the adjusted temperature changes and makes fine adjustments to ensure that the final temperature difference ΔT_final remains within the set tolerance range. The regulation formula is ΔT_final=ΔT_pos-η*(Q_add(i) / C_thermal), where η is the efficiency factor and C_thermal is the thermal capacity.

[0045] Preferably, the feedback monitoring station comprises:

[0046] Temperature data collector, used to continuously collect real-time temperature T_real at multiple locations within the battery cabinet;

[0047] The comparison and analysis unit is connected to the temperature data collector, compares the received real-time temperature T_real with the preset target temperature T_target, and calculates the temperature deviation ΔT_dev. The calculation formula is ΔT_dev=T_real-T_target;

[0048] The intensity adjustment controller receives the ΔT_dev value from the comparison and analysis unit and adjusts the working intensity P_adj of the heating element according to the temperature deviation. The adjustment formula is P_adj=P_base+κ*ΔT_dev, where P_base is the base heating power and κ is the adjustment coefficient;

[0049] The execution instruction generator is connected to the intensity adjustment controller, generates a new heating instruction I_new based on the adjusted heating power P_adj, and sends it back to the dynamic adjustment device to update the heat distribution. The instruction generation formula is I_new=f(P_adj), where f represents the mapping function from power to instruction.

[0050] Preferably, the feedback monitoring station forms a closed loop with the initial sensing unit to ensure the stable operation and management of the entire system, including:

[0051] Temperature verification interface, used to receive real-time temperature data T_real from the feedback monitoring station and compare it with the ambient temperature T_env initially obtained by the sensing unit;

[0052] The deviation calculation unit is connected to the temperature verification interface and calculates the new deviation ΔT_new between the real-time temperature T_real and the preset target temperature T_target. The calculation formula is ΔT_new=T_real-T_target;

[0053] The cyclic adjustment controller receives the new deviation ΔT_new from the deviation calculation unit and calculates the correction coefficient C_corr based on the old deviation ΔT_old recorded previously. The correction formula is C_corr = (ΔT_new - ΔT_old) / ΔT_old;

[0054] The instruction update module is connected to the loop adjustment controller and updates the initial parameter setting P_set of the sensing unit according to the correction coefficient C_corr. The update formula is P_set_updated=P_set*(1+C_corr). The updated parameters are sent back to the sensing unit to complete the closed-loop control.

[0055] Technical effects and advantages of the present invention: The thermal management system proposed by the present invention, which can regulate the temperature inside a split battery cabinet, has the following advantages over the prior art:

[0056] The present invention achieves precise control of the temperature inside the battery cabinet by introducing a dynamic adjustment device and a closed-loop feedback mechanism; the sensing unit monitors environmental changes in real time and quickly starts the heating operation. The dynamic adjustment device automatically optimizes heat distribution based on the actual temperature differences at different locations in the battery cabinet to ensure uniform heat distribution. The feedback monitoring station forms a closed loop with the initial sensing unit, continuously monitoring and adjusting the heating intensity in a timely manner to ensure stable operation and efficient management of the system, significantly improving the effectiveness and reliability of temperature management in the battery cabinet under extremely low temperature conditions, ensuring the optimal working state of the battery and extending its service life. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1This is a block diagram of a thermal management system capable of regulating the temperature inside a split battery cabinet according to the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0059] The present invention provides Figure 1 A thermal management system capable of regulating the temperature inside a split battery cabinet is shown, comprising: a sensing unit, an analysis and processing center, a command generator, a heating element array, an energy conversion component, a heat conduction network, a dynamic adjustment device, and a feedback monitoring station.

[0060] In this embodiment, the sensing unit monitors environmental changes in real time and quickly initiates the heating operation. The dynamic adjustment device automatically optimizes heat distribution based on the actual temperature differences at different locations in the battery cabinet to ensure uniform heat distribution. The feedback monitoring station and the initial sensing unit form a closed loop, continuously monitoring and adjusting the heating intensity in a timely manner to ensure stable operation and efficient management of the system. This significantly improves the effectiveness and reliability of temperature management in the battery cabinet under extreme low temperature conditions, ensures the optimal working state of the batteries, and extends their service life. The details are as follows:

[0061] In this embodiment, the sensing unit activated in response to changes in environmental conditions is connected to an analysis and processing center, which evaluates whether a heating operation needs to be activated based on data provided by the sensing unit.

[0062] Furthermore, the sensing unit includes:

[0063] Environmental parameter detectors are used to obtain the ambient temperature T_env in real time, ensuring the system can quickly respond to external temperature changes. Accurate temperature monitoring provides accurate data for subsequent heating decisions.

[0064] The comparison component is used to receive the temperature value T_env from the environmental parameter detector and compare it with the preset low temperature threshold T_min. If T_env is less than T_min, an activation signal S_act is generated. This step ensures that the heating operation is started only when necessary, improves energy utilization efficiency and reduces unnecessary heating.

[0065] After receiving the activation signal S_act from the comparison component, the time delay controller delays the output of the control signal C_ctrl to the subsequent modules according to the preset time interval Δt. The introduction of the time delay can avoid malfunction caused by instantaneous temperature fluctuations and enhance the stability and reliability of the system.

[0066] After receiving the control signal C_ctrl from the time delay controller, the intensity regulator calculates the required heating power P_heat using the formula P_heat = α * (T_target - T_env), where α is the proportionality factor and T_target is the target maintenance temperature. This step dynamically adjusts the heating power to ensure that the heat provided meets actual demand, improving heating efficiency and temperature control accuracy.

[0067] Furthermore, the analysis and processing center includes:

[0068] The data receiving interface is used to receive data D_sense from the sensing unit, including but not limited to the ambient temperature T_env and the temperature inside the battery cabinet T_cab. As the data entry, this interface ensures the timely transmission of all temperature information, supporting subsequent modules to make accurate heating decisions.

[0069] The difference calculation unit is connected to the data receiving interface and is used to calculate the difference ΔT_low between T_env and the preset lower operating temperature limit T_min, and the difference ΔT_high between T_cab and the preset upper operating temperature limit T_max. The calculation formulas are ΔT_low = T_min - T_env and ΔT_high = T_cab - T_max. This step provides a quantitative assessment of the current temperature state and provides necessary input for the decision logic module.

[0070] The decision logic module receives the ΔT_low and ΔT_high values ​​from the difference calculation unit. When ΔT_low > 0 or ΔT_high < 0, the decision logic module generates a heating request signal R_heat. This module is responsible for comprehensively evaluating multiple temperature differences to determine whether to initiate a heating operation to ensure that the temperature inside the battery cabinet remains within an appropriate range.

[0071] The priority determiner receives the heating request signal R_heat from the decision logic module and checks whether there are other operation instructions O_opr. If no other operation instructions with higher priority exist, the heating request is approved and a confirmation signal A_conf is sent to the instruction generator. This step ensures that the heating operation does not conflict with other critical operations and maintains the overall operating order of the system.

[0072] The thermal management system in this embodiment can not only efficiently respond to changes in environmental conditions, but also accurately control the temperature inside the battery cabinet, ensuring that the batteries always operate within the optimal temperature range, thereby improving battery performance and extending their service life.

[0073] In this embodiment, the analysis and processing center is coupled to a command generator. When heating is determined to be necessary, the command generator sends an activation signal to a distributed array of heating elements. Upon receiving the signal from the command generator, each member of the array triggers an energy conversion component connected thereto to convert electrical energy into thermal energy.

[0074] Furthermore, the instruction generator includes:

[0075] The signal preparation unit is used to receive the confirmation signal A_conf from the analysis and processing center and prepare the activation command C_cmd based on the signal; this step ensures that the activation command is generated only when the system confirms that heating is required, avoiding unnecessary heating operations and improving the system's response efficiency and energy utilization efficiency.

[0076] The address distributor is connected to the signal preparation unit and is used to assign a unique address identifier ID_addr to each distributed heating element; in this way, each heating element can independently identify and respond to a specific activation command, ensuring the accuracy and targeting of the heating operation and avoiding interference between multiple elements.

[0077] The power setting module, connected to the address distributor, calculates the required heating power P_set based on the preset heating mode M_heat and the current ambient temperature T_env. The calculation formula is P_set = β * (T_target - T_env), where β is the proportional coefficient. This step dynamically adjusts the heating power to ensure that the heat provided meets actual needs, improving heating efficiency and temperature control accuracy while reducing energy waste.

[0078] The command transmitter receives the P_set value from the power setting module and the ID_addr information from the address distributor, combines them into a complete activation signal S_actv, and sends S_actv to the corresponding heating element. This step ensures that each heating element receives the precise heating instruction that matches its address, enabling effective management and control of the distributed heating element array.

[0079] Furthermore, the heating element array comprises:

[0080] The signal receiving port is used to receive the activation signal S_actv from the instruction generator, which contains the address identifier ID_addr and the set heating power P_set for a specific heating element; this step ensures that each heating element can accurately receive the heating instruction customized for it, thereby improving the targeting and accuracy of the heating operation.

[0081] The verification module is connected to the signal receiving port to verify whether the ID_addr in the received S_actv matches its own address. Through the verification mechanism, it ensures that only the target heating element responds to the activation signal, enhancing the reliability and safety of the system and avoiding misoperation.

[0082] The current regulation unit receives the activation signal S_actv confirmed by the verification module and adjusts the current I_adj supplied to the energy conversion component according to the P_set value therein. The current adjustment formula is I_adj=P_set / V_supply, where V_supply is the supply voltage. This step ensures that each heating element is heated according to the set power by accurately adjusting the current, thereby improving the heating efficiency and stability.

[0083] The energy conversion component is connected to the current regulation unit, receives the adjusted current I_adj, and converts it into heat energy Q_heat. The conversion relationship follows Joule's law and the calculation formula is Q_heat= *R_heater*t, where R_heater is the heating resistance and t is the time. This step efficiently converts electrical energy into thermal energy, ensuring a fast and stable heating process and meeting the temperature requirements within the battery cabinet.

[0084] Furthermore, the energy conversion component includes:

[0085] The power receiving interface is used to receive the adjusted current I_adj from the current regulation unit; this interface serves as a current input point, ensuring that the current can be stably and safely transmitted to the subsequent heating element, supporting efficient energy conversion.

[0086] The resistance heating element is connected to the power receiving interface and converts the received current I_adj into heat energy Q_heat through the internal resistor R_heater. The conversion formula is Q_heat= *R_heater; This step achieves efficient conversion from electrical energy to thermal energy, ensuring the efficiency and reliability of the heating element.

[0087] The heat transfer interface, connected to the resistive heating element, is responsible for efficiently transferring the generated heat energy Q_heat to the heat conduction network. The transfer efficiency η_trans is calculated as η_trans = Q_delivered / Q_heat, where Q_delivered is the actual amount of heat transferred to the heat conduction network. This step ensures the effective transfer of heat energy, reduces heat loss, and improves the heating efficiency of the entire system.

[0088] The temperature monitor, connected to the heat transfer interface, monitors the temperature change (T_change) during the transfer process in real time and adjusts the operating state of the resistance heating element based on temperature feedback. The adjustment formula is R_heater_adjusted = R_heater * (1 + μ * T_change), where μ is the temperature sensitivity coefficient. Through real-time monitoring and feedback adjustment, precise temperature control and system stability are ensured, preventing overheating or insufficient heating.

[0089] The command generator and heating element array in this embodiment not only efficiently respond to heating requests but also precisely control the operating status of each heating element, ensuring the temperature within the battery cabinet remains within the optimal range. Furthermore, through real-time monitoring and feedback adjustments, the system maintains stable heating performance in extremely low-temperature environments, improving battery efficiency and lifespan.

[0090] In this embodiment, the energy conversion assembly is connected to a heat conduction network, which is connected to a dynamic adjustment device that automatically optimizes heat distribution based on temperature differences within the battery cabinet.

[0091] Furthermore, the heat conduction network includes:

[0092] The heat receiving interface is used to directly receive the thermal energy Q_heat generated by the energy conversion component and initially homogenize it; this step ensures the uniform distribution of the initial heat, provides a basis for subsequent precise heat transfer, and reduces the possibility of local overheating or insufficient heating.

[0093] The thermal medium distributor, connected to the heat receiving interface, transfers heat energy through different paths based on the internal structure of the battery cabinet and the preset heat distribution mode D_mode. The distributor ensures that the heat flow F_path on each path matches the requirements of the required location. The calculation formula is F_path = Q_heat / N_paths, where N_paths is the number of heat conduction paths. This step achieves reasonable heat distribution, ensuring that each location can receive the required heat, and improving overall heating efficiency and uniformity.

[0094] The multi-layer heat conducting plate receives the heat flow F_path from the thermal medium distributor. The multi-layer heat conducting plate is composed of several layers of high-efficiency thermal conductive material. Each layer has optimized contact to minimize the thermal resistance R_contact. The thermal resistance is calculated as R_contact = δ / (k*A), where δ is the interlayer contact thickness, k is the thermal conductivity, and A is the contact area. This step minimizes heat loss through the use of multiple layers of high-efficiency thermal conductive material and optimized contact design, ensuring that heat is quickly and evenly transferred to the entire battery cabinet, thereby improving the system's thermal conduction efficiency.

[0095] The temperature balancing controller, connected to the multi-layer heat transfer plates, monitors and adjusts the temperature difference ΔT_layer between each layer. Based on real-time temperature feedback, the controller adjusts the operating state of the heat transfer plates to ensure that ΔT_layer ≤ T_tolerance, where T_tolerance is the set temperature tolerance. This step ensures consistent and stable temperature within the battery cabinet, preventing battery performance degradation or damage caused by temperature unevenness, and improving battery efficiency and lifespan.

[0096] Furthermore, the dynamic adjustment device includes:

[0097] The temperature difference detector is used to monitor the temperature T_pos at different locations within the battery cabinet in real time and calculate the temperature difference ΔT_pos between each location. The calculation formula is ΔT_pos = |T_pos(i) - T_pos_avg|, where T_pos(i) is the actual temperature at a certain location and T_pos_avg is the average temperature of all locations. This step provides accurate monitoring of the temperature distribution within the battery cabinet, providing data support for subsequent heat distribution optimization and ensuring that the system can respond to temperature changes in a timely manner.

[0098] The heat demand estimator, connected to the temperature difference detector, estimates the additional heat Q_add required for each location based on ΔT_pos. The evaluation formula is Q_add(i)=γ*ΔT_pos(i), where γ is the heat compensation coefficient. This step determines the specific heat demand at each location through a quantitative assessment of temperature differences, ensuring the targeted and effective heating operation and avoiding unnecessary energy waste.

[0099] The distribution optimization controller receives Q_add data from the heat demand evaluator and optimizes the heat flux F_opt on each heat conduction path based on the current heat distribution. The optimization formula is F_opt(path)=F_path+Q_add(i) / N_paths_connected, where N_paths_connected is the number of heat conduction paths connected to the location. This step ensures that each location receives sufficient heat by dynamically adjusting the heat flow distribution, maintaining temperature consistency within the battery cabinet, and improving heating efficiency and temperature control accuracy.

[0100] The feedback regulation unit, connected to the allocation optimization controller, continuously monitors the adjusted temperature changes and makes fine adjustments to ensure that the final temperature difference ΔT_final remains within the set tolerance range. The adjustment formula is ΔT_final = ΔT_pos - η * (Q_add(i) / C_thermal), where η is the efficiency factor and C_thermal is the thermal capacity. This step ensures that the system maintains temperature stability during operation through real-time feedback and fine-tuning mechanisms, enhancing system reliability and adaptability and preventing temperature fluctuations from affecting battery performance.

[0101] The heat conduction network and dynamic adjustment device in this embodiment can not only efficiently transfer and distribute heat, but also automatically optimize heat distribution based on temperature differences within the battery cabinet. Specifically:

[0102] The heat conduction network ensures the initial uniformity and efficient transfer of heat. The design of multi-layer heat conducting plates and the monitoring of the temperature equalization controller maintain the consistency and stability of the temperature inside the battery cabinet.

[0103] The dynamic adjustment device ensures that each location receives the required heat by real-time monitoring, evaluation and optimization of heat distribution, while maintaining precise temperature control through a feedback adjustment mechanism, thereby improving the reliability and adaptability of the system.

[0104] In this embodiment, the above-mentioned dynamic adjustment device also interacts with a feedback monitoring station to continuously monitor the temperature and adjust the heating intensity in a timely manner. The feedback monitoring station forms a closed loop with the initial sensing unit to ensure the stable operation and management of the entire system.

[0105] Furthermore, the feedback monitoring station includes:

[0106] The temperature data collector is used to continuously collect the real-time temperature T_real at multiple locations within the battery cabinet. This step ensures real-time monitoring of temperature changes within the battery cabinet, provides accurate temperature data, and supports subsequent modules to make accurate heating adjustments.

[0107] The comparison and analysis unit, connected to the temperature data collector, compares the received real-time temperature T_real with the preset target temperature T_target and calculates the temperature deviation ΔT_dev using the formula ΔT_dev = T_real - T_target. This step quantifies the temperature deviation and provides the necessary input for the intensity regulation controller, ensuring that the system can make precise heating adjustments based on the actual temperature difference.

[0108] The intensity regulation controller receives the ΔT_dev value from the comparison and analysis unit and adjusts the operating intensity P_adj of the heating element according to the temperature deviation. The adjustment formula is P_adj = P_base + κ * ΔT_dev, where P_base is the baseline heating power and κ is the adjustment coefficient. This step dynamically adjusts the heating intensity to ensure that the heat provided meets actual needs, improves the system's response speed and temperature control accuracy, and avoids overheating or insufficient heating.

[0109] The execution command generator, connected to the intensity adjustment controller, generates a new heating command, I_new, based on the adjusted heating power, P_adj. This command is sent back to the dynamic adjustment device to update the heat distribution. The command generation formula is I_new = f(P_adj), where f represents the mapping function from power to command. This step ensures the timely update and transmission of heating commands, allowing the dynamic adjustment device to optimize heat distribution based on the latest temperature requirements, improving the flexibility and adaptability of the system.

[0110] The feedback monitoring station forms a closed loop with the initial sensing unit to ensure the stable operation and management of the entire system, including:

[0111] The temperature verification interface is used to receive real-time temperature data T_real from the feedback monitoring station and compare it with the ambient temperature T_env initially obtained by the sensing unit. This step ensures the consistency of the data from the feedback monitoring station and the initial sensing unit data, enhances the reliability and accuracy of the system, and avoids erroneous operations caused by inconsistent data.

[0112] The deviation calculation unit, connected to the temperature verification interface, calculates the new deviation ΔT_new between the real-time temperature T_real and the preset target temperature T_target using the formula ΔT_new = T_real - T_target. This step provides the necessary input for the loop adjustment controller by quantifying the deviation between the old and new temperatures, ensuring that the system can make accurate adjustments based on the latest temperature changes.

[0113] The cyclic adjustment controller receives the new deviation ΔT_new from the deviation calculation unit and combines it with the previously recorded old deviation ΔT_old to calculate the correction coefficient C_corr. The correction formula is C_corr = (ΔT_new - ΔT_old) / ΔT_old. This step ensures that the system can be optimized and adjusted according to the temperature change trend by dynamically adjusting the correction coefficient, thereby improving the system stability and response speed.

[0114] The command update module, connected to the loop adjustment controller, updates the initial sensing unit parameter settings, P_set, based on the correction coefficient, C_corr, using the formula P_set_updated = P_set*(1+C_corr). The updated parameters are then sent back to the sensing unit, completing closed-loop control. This step dynamically updates the sensing unit parameters, ensuring the entire system maintains optimal operating conditions during operation and enhancing its adaptability and stability.

[0115] Through the above design, the feedback monitoring station in this embodiment can not only continuously monitor the temperature changes in the battery cabinet and adjust the heating intensity in a timely manner, but also form a closed-loop control system with the initial sensing unit to ensure the stable operation and efficient management of the entire system.

[0116] The feedback monitoring station ensures the accuracy and effectiveness of heating operations through real-time temperature data collection, deviation calculation and heating intensity adjustment, thereby improving the system's response speed and temperature control accuracy.

[0117] The closed-loop control system achieves self-adjustment and optimization through temperature verification, deviation calculation and parameter update, enhances the system's stability and adaptability, and ensures that the temperature inside the battery cabinet always remains within the optimal range.

[0118] These innovative designs significantly improve the effectiveness and reliability of temperature management in battery cabinets under extremely low temperature conditions, ensuring the optimal working condition of the batteries and extending their service life.

[0119] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A thermal management system capable of regulating the temperature inside a split battery cabinet, characterized in that: include: a sensing unit activated in response to changes in environmental conditions, the sensing unit being connected to an analysis and processing center which evaluates whether activation of a heating operation is necessary based on data provided by the sensing unit; The analysis and processing center is coupled to a command generator. When it is determined that heating is required, the command generator sends an activation signal to a distributed array of heating elements. After receiving the signal from the command generator, each member of the heating element array triggers an energy conversion component connected thereto to convert electrical energy into thermal energy. The energy conversion assembly is connected to a heat conduction network, which is connected to a dynamic adjustment device that automatically optimizes heat distribution based on temperature differences within the battery cabinet. The heat conduction network includes: The heat receiving interface is used to directly receive the heat energy Q_heat generated by the energy conversion component and initially homogenize it; The thermal medium distributor is connected to the heat receiving interface and transfers heat energy through different paths based on the internal structure of the battery cabinet and the preset heat distribution mode D_mode. The distributor ensures that the heat flow F_path on each path matches the requirements of the required location. The calculation formula is F_path = Q_heat / N_paths, where N_paths is the number of heat conduction paths. The multi-layer heat conducting plate receives the heat flow F_path from the heat conducting medium distributor. The multi-layer heat conducting plate is composed of several layers of high-efficiency heat conducting materials. There is optimized contact between each layer to minimize the thermal resistance R_contact. The thermal resistance is calculated as R_contact=δ / (k*A), where δ is the contact thickness between the layers, k is the thermal conductivity, and A is the contact area. The temperature balance controller is connected to the multi-layer heat transfer plate to monitor and adjust the temperature difference ΔT_layer between each layer. The controller adjusts the working state of the heat transfer plate based on real-time temperature feedback to make ΔT_layer ≤ T_tolerance, where T_tolerance is the set temperature tolerance; The dynamic adjustment device also interacts with a feedback monitoring station to continuously monitor the real-time temperature of multiple locations in the battery cabinet and adjust the heating intensity in a timely manner. The feedback monitoring station forms a closed loop with the initial sensing unit to ensure the stable operation and management of the entire system.

2. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 1, characterized in that: The sensing unit comprises: Environmental parameter detector, used to obtain the ambient temperature T_env; a comparison component, configured to receive a temperature value T_env from an environmental parameter detector and compare it with a preset low temperature threshold T_min, and generate an activation signal S_act if T_env is less than T_min; The time delay controller, after receiving the activation signal S_act from the comparison component, delays the output of the control signal C_ctrl to the subsequent module according to the preset time interval Δt; After receiving the control signal C_ctrl from the time delay controller, the intensity regulator calculates the heating power P_heat that needs to be provided through the formula P_heat=α*(T_target-T_env), where α is the proportional coefficient and T_target is the target maintenance temperature.

3. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 2, characterized in that: The analysis and processing center includes: Data receiving interface, used to receive data D_sense from the sensing unit, including the ambient temperature T_env and the temperature inside the battery cabinet T_cab; a difference calculation unit connected to the data receiving interface, configured to calculate a difference ΔT_low between T_env and a preset lower operating temperature limit T_min, and a difference ΔT_high between T_cab and a preset upper operating temperature limit T_max, wherein the calculation formulas are ΔT_low=T_min-T_env and ΔT_high=T_cab-T_max; A decision logic module receives the ΔT_low and ΔT_high values ​​from the difference calculation unit, and generates a heating request signal R_heat when ΔT_low>0 or ΔT_high<0; The priority judge receives the heating request signal R_heat from the decision logic module and checks whether there are other operation instructions O_opr. If there are no other operation instructions with higher priority, the heating request is allowed to pass and a confirmation signal A_conf is sent to the instruction generator.

4. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 3, characterized in that: The instruction generator comprises: A signal preparation unit, configured to receive a confirmation signal A_conf from the analysis and processing center and prepare an activation command C_cmd according to the signal; An address distributor, connected to the signal preparation unit, for distributing a unique address identifier ID_addr to each distributed heating element; The power setting module is connected to the address distributor and calculates the required heating power P_set according to the preset heating mode M_heat and the current ambient temperature T_env. The calculation formula is P_set=β*(T_target-T_env), where β is the proportional coefficient; The command transmitter receives the P_set value from the power setting module and the ID_addr information from the address distributor, combines them into a complete activation signal S_actv, and sends S_actv to the corresponding heating element.

5. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 4, characterized in that: The heating element array comprises: A signal receiving port is used to receive an activation signal S_actv from the instruction generator, where the signal includes an address identifier ID_addr for a specific heating element and a set heating power P_set; Verification module, connected to the signal receiving port, verifies whether the ID_addr in the received S_actv matches its own address; The current regulation unit receives the activation signal S_actv confirmed by the verification module and adjusts the current I_adj supplied to the energy conversion component according to the value P_set therein. The current adjustment formula is I_adj=P_set / V_supply, where V_supply is the supply voltage; The energy conversion component is connected to the current regulation unit, receives the adjusted current I_adj, and converts it into heat energy Q_heat. The conversion relationship follows Joule's law, and the calculation formula is Q_heat= *R_heater*t, where R_heater is the heating resistance and t is the time.

6. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 5, characterized in that: The energy conversion component comprises: An electric energy receiving interface, configured to receive the adjusted current I_adj from the current regulating unit; The resistance heating element is connected to the power receiving interface and converts the received current I_adj into heat energy Q_heat through the internal resistor R_heater. The conversion formula is Q_heat= *R_heater; The heat transfer interface is connected to the resistance heating element and is responsible for efficiently transferring the generated heat energy Q_heat to the heat conduction network. The transfer efficiency η_trans is calculated as η_trans=Q_delivered / Q_heat, where Q_delivered is the actual heat transferred to the heat conduction network. The temperature monitor is connected to the heat transfer interface to monitor the temperature change T_change during the transfer process in real time, and adjust the working state of the resistance heating element according to the temperature feedback. The adjustment formula is R_heater_adjusted=R_heater*(1+μ*T_change), where μ is the temperature sensitivity coefficient.

7. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 6, characterized in that: The dynamic adjustment device comprises: The temperature difference detector is used to monitor the temperature T_pos at different locations in the battery cabinet in real time and calculate the temperature difference ΔT_pos between each location. The calculation formula is ΔT_pos = |T_pos(i) - T_pos_avg|, where T_pos(i) is the actual temperature at a certain location and T_pos_avg is the average temperature of all locations. A heat demand estimator is connected to the temperature difference detector and estimates the additional heat required for each position Q_add based on ΔT_pos. The evaluation formula is Q_add(i)=γ*ΔT_pos(i), where γ is the heat compensation coefficient; The allocation optimization controller receives the Q_add data from the heat demand estimator and optimizes the heat flow F_opt on each heat conduction path according to the current heat distribution. The optimization formula is F_opt(path)=F_path+Q_add(i) / N_paths_connected, where N_paths_connected is the number of heat conduction paths connected to the location. The feedback regulation unit is connected to the distribution optimization controller, continuously monitors the adjusted temperature changes and makes fine adjustments to ensure that the final temperature difference ΔT_final remains within the set tolerance range. The regulation formula is ΔT_final=ΔT_pos-η*(Q_add(i) / C_thermal), where η is the efficiency factor and C_thermal is the thermal capacity.

8. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 7, characterized in that: The feedback monitoring station comprises: Temperature data collector, used to continuously collect real-time temperature T_real at multiple locations within the battery cabinet; The comparison and analysis unit is connected to the temperature data collector, compares the received real-time temperature T_real with the preset target temperature T_target, and calculates the temperature deviation ΔT_dev. The calculation formula is ΔT_dev=T_real-T_target; The intensity adjustment controller receives the ΔT_dev value from the comparison and analysis unit and adjusts the working intensity P_adj of the heating element according to the temperature deviation. The adjustment formula is P_adj=P_base+κ*ΔT_dev, where P_base is the base heating power and κ is the adjustment coefficient; The execution instruction generator is connected to the intensity adjustment controller, generates a new heating instruction I_new based on the adjusted heating power P_adj, and sends it back to the dynamic adjustment device to update the heat distribution. The instruction generation formula is I_new=f(P_adj), where f represents the mapping function from power to instruction.

9. The thermal management system capable of regulating the temperature inside a split-type battery cabinet according to claim 8, characterized in that: The feedback monitoring station forms a closed loop with the initial sensing unit to ensure the stable operation and management of the entire system, including: Temperature verification interface, used to receive real-time temperature data T_real from the feedback monitoring station and compare it with the ambient temperature T_env initially obtained by the sensing unit; The deviation calculation unit is connected to the temperature verification interface and calculates the new deviation ΔT_new between the real-time temperature T_real and the preset target temperature T_target. The calculation formula is ΔT_new=T_real-T_target; The cyclic adjustment controller receives the new deviation ΔT_new from the deviation calculation unit and calculates the correction coefficient C_corr based on the old deviation ΔT_old recorded previously. The correction formula is C_corr = (ΔT_new - ΔT_old) / ΔT_old; The instruction update module is connected to the loop adjustment controller and updates the initial parameter setting P_set of the sensing unit according to the correction coefficient C_corr. The update formula is P_set_updated=P_set*(1+C_corr). The updated parameters are sent back to the sensing unit to complete the closed-loop control.

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