A method for intelligent start-stop thermal management of a new energy ship battery

Abstract

The application provides a new energy ship battery intelligent start-stop heat management method, and belongs to the technical field of battery heat management. Three types of operation data of battery state parameters, ship working condition parameters and marine environment parameters are synchronously collected; the current operation condition of the ship is identified; the dynamic start-stop threshold of cooling and heating is generated in real time based on the battery reference temperature and the coupling calculation of the collected data; the differential temperature control strategy corresponding to the current operation condition is matched, the start-stop control instruction and the stepless power regulation instruction of the heat management system are generated in combination with the dynamic start-stop threshold; the heat management mode of liquid cooling and phase change material is adopted to drive the actuator; the battery temperature, the single cell temperature difference and the system energy consumption data after temperature control execution are collected, and the calculation parameters of the dynamic start-stop threshold are iteratively corrected; and the ship battery heat management condition database is constructed. The application improves the adaptability of the ship battery heat management method to the ship working condition and the marine environment, and improves the heat management effect.

Description

Technical Field

[0001] This invention belongs to the field of battery thermal management technology. Specifically, this invention relates to a method for intelligent start-stop thermal management of batteries for new energy ships. Background Technology

[0002] With the accelerated green transformation of global shipping, pure electric and hybrid new energy vessels have become the mainstream development direction for inland waterway shipping, coastal transportation, and port operations. As the core power source of new energy vessels, the operational stability of power batteries directly determines the safety and economic efficiency of navigation. Ship power batteries operate under unique marine conditions, facing complex challenges such as wide temperature ranges, drastic fluctuations in navigation loads, hull pitching and vibration, and high humidity and salt spray. The battery's heat generation rate and heat dissipation conditions are constantly changing.

[0003] Chinese Patent 120453572A discloses a marine battery box and a vessel, including a battery system, a high-voltage control box, a thermal management system, and a fire protection system. The battery system consists of multiple battery packs, each containing a battery unit (BMU) and a fire detector. The high-voltage control box includes a BCU, a discharge circuit with a discharge switch, a charging circuit with a charging switch, and a thermal management circuit with a thermal management switch. One end of each of the discharge circuit, charging circuit, and thermal management circuit is connected to the battery system, and the other end is connected to the discharge interface, charging interface, and thermal management system, respectively. The BCU controls the closing of the charging switch or discharge switch according to the charging / discharging commands sent by the vessel's energy management system to meet the vessel's power needs. When the BMU detects an abnormal battery pack temperature, the BCU controls the thermal management switch to close; when the fire detector detects thermal runaway of the battery pack, the fire protection system extinguishes the fire.

[0004] Existing technologies for thermal management control of ships employ fixed threshold regulation, which has low adaptability to ship operating conditions and marine environment, thus affecting the effectiveness of thermal management. Summary of the Invention

[0005] The present invention aims to provide a method for intelligent start-stop thermal management of new energy ship batteries, so as to improve the adaptability of ship battery thermal management methods to ship operating conditions and marine environment, and improve the effectiveness of thermal management.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] This invention provides a method for intelligent start-stop thermal management of batteries in new energy ships, comprising the following steps:

[0008] Step 1: Synchronously collect three types of operational data: battery status parameters, ship operating condition parameters, and marine environmental parameters, and transmit them to the main control unit via the ship's CAN bus;

[0009] Step 2: Identify the ship's current operating condition, and based on the battery reference temperature, perform coupled calculations with the collected data to generate dynamic start-stop thresholds for cooling and heating in real time.

[0010] Step 3: Match the differentiated temperature control strategy corresponding to the current operating condition, and generate start-stop control commands and stepless power regulation commands for the thermal management system by combining the dynamic start-stop threshold;

[0011] Step 4: Employ a thermal management method combining liquid cooling and phase change materials to drive the actuators;

[0012] Step 5: Collect battery temperature, individual cell temperature difference and system energy consumption data after temperature control is implemented, compare with the preset optimal temperature control target range, and iteratively correct the calculation parameters of the dynamic start-stop threshold; at the same time, record the temperature control effect under different sea conditions and operating conditions, and build a database of ship battery thermal management operating conditions.

[0013] In step one, the battery status parameters include the highest temperature, lowest temperature, average temperature, temperature rise rate, capacity, charge / discharge rate, internal resistance, and temperature difference between individual cells; the ship operating parameters include navigation status, power load, sailing speed, and battery compartment sealing temperature; and the marine environment parameters include ambient temperature, air humidity, sea wind speed, and seawater temperature.

[0014] In step two, the ship's dynamic load factor is the ratio of the real-time output power of the propulsion motor to its rated power.

[0015] In step two, the formula for calculating the dynamic cooling activation threshold is:

[0016] ;

[0017] The formula for calculating the dynamic cooling shutdown threshold is:

[0018] ;

[0019] in The reference temperature for standard battery cooling is set. The standard cooling shutdown reference temperature for the battery. For the real-time temperature rise rate of the battery, For ship dynamic load factor, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, load correction factor, and environmental correction factor, respectively.

[0020] In step two, the formula for calculating the dynamic heating activation threshold is:

[0021] ;

[0022] The formula for calculating the dynamic heating shut-off threshold is:

[0023] ;

[0024] in Set the reference temperature for standard battery heating. The standard heating shut-off reference temperature for the battery is [temperature value missing]. For the real-time temperature rise rate of the battery, For battery power, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, battery charge correction factor, and environmental correction factor, respectively.

[0025] In step two, the operating conditions are divided into four categories: parking and standby, low-speed cruising, heavy-load operation, and extreme temperature range; the corresponding differentiated temperature control strategy in step three is as follows:

[0026] In standby mode, the cooling activation threshold is raised and the heating trigger sensitivity is reduced. Low-power liquid cooling cycle is only activated for temperature control when the battery temperature fluctuates abnormally or the temperature difference between individual cells exceeds the standard.

[0027] Under low-speed cruising conditions, the liquid cooling flow rate and fan speed are dynamically and finely adjusted to control the thermal management system to operate within a preset rated power range and maintain stable battery temperature.

[0028] Under heavy-load operating conditions, the cooling activation threshold is reduced, and the liquid cooling cycle power is increased to the preset value of the rated power. In conjunction with phase change materials, the accumulated heat of the battery is absorbed, and the maximum temperature of the battery and the temperature difference between individual cells are controlled.

[0029] Under extreme temperature conditions, the cooling system is activated in advance in high-temperature marine environments to suppress heat accumulation, while a low-heat-consumption heating mode is adopted in low-temperature marine environments, and the heating time and power are dynamically adjusted according to the battery charge.

[0030] In step three, a fuzzy PID adaptive control algorithm is used to generate stepless power regulation commands. The average battery temperature, maximum temperature difference of individual cells, and temperature rise rate are used as inputs. The proportional, integral, and derivative parameters of the PID controller are corrected in real time through preset fuzzy rules to regulate the start-up and shutdown timing and operating power of the thermal management system.

[0031] Step three also includes intelligent anti-start-stop oscillation processing: setting dynamic start-stop hysteresis interval and operating condition delay judgment logic; the width of the dynamic start-stop hysteresis interval is adjusted in real time according to the current operating condition, widening the hysteresis interval under high dynamic operating conditions and narrowing the hysteresis interval under steady-state operating conditions; the operating condition delay judgment logic is that the start-stop command is triggered only when the battery temperature reaches the corresponding start-stop threshold and the duration meets the preset conditions.

[0032] In step four, the actuators include a liquid-cooled circulating pump, a variable frequency cooling fan, a PTC heating module, and a flow regulating valve; phase change material is laid in the gaps between battery modules and at the bottom of the modules.

[0033] In step five, machine learning algorithms are used to iteratively correct the calculation parameters of the dynamic start-stop threshold, and the temperature control strategy under different sea conditions and operating conditions is continuously updated based on the ship battery thermal management operating condition database.

[0034] The technical effects of this invention are as follows:

[0035] (1) This invention has the advantages of multi-parameter coupled dynamic threshold regulation and high temperature control accuracy. Unlike the coarse control mode of fixed start-stop threshold in traditional ship battery thermal management, this invention is based on three types of real-time operating data: battery state parameters, ship operating condition parameters, and marine environment parameters. Through multi-dimensional parameter coupling calculation such as temperature rise rate, power load, ambient temperature, and battery SOC, a dedicated dynamic cooling and heating start-stop threshold model is constructed, which can update the threshold parameters in real time according to the ship's operating status and marine environment. It effectively solves the problems of traditional fixed threshold control being unable to adapt to complex marine conditions, lagging temperature regulation, and poor consistency of individual cells, and greatly improves the temperature control accuracy of ship batteries in all scenarios.

[0036] (2) This invention improves the adaptability of ship batteries to different operating conditions and covers a wide range of scenarios. It accurately divides the four core operating conditions of ships into four categories: berthing and standby, low-speed cruising, heavy-load operation, and extreme temperature range, and matches exclusive differentiated temperature control strategies for the battery thermal load characteristics and navigation requirements of different operating conditions. It comprehensively covers the scenarios of normal navigation, operation, berthing and extreme sea environment of ships, and solves the problems of traditional thermal management systems having single control logic, being unable to adapt to dynamic switching of ship operating conditions, and failing temperature control in extreme sea conditions. Its adaptability far exceeds that of traditional general-purpose temperature control solutions.

[0037] (3) The present invention has a good balance between temperature control and energy consumption. It adopts a composite thermal management architecture that combines active liquid cooling temperature control with passive phase change temperature equalization. On the active side, through a variable frequency liquid cooling pump, a variable speed fan, and a stepless power PTC heating module, it achieves precise and rapid active temperature control intervention, and can specifically adjust the flow rate of each battery module branch to accurately control the temperature of high-temperature modules. On the passive side, through the paraffin-based phase change material laid in the gaps and bottom of the battery modules, it utilizes the characteristics of melting heat absorption and solidification heat release to smooth out battery temperature peaks, weaken temperature fluctuations, and optimize the module temperature equalization effect. It significantly reduces the overall operating energy consumption of the thermal management system, achieves a two-way balance between high-precision temperature control and low-energy operation, and meets the core requirements of energy-saving navigation of ships.

[0038] (4) This invention features an intelligent anti-vibration mechanism, resulting in high system stability. Addressing the issues of complex marine environments, wind and wave interference, sensor data noise, and frequent fluctuations in operating conditions that can lead to frequent start-ups and shutdowns of the thermal management system, temperature control oscillations, and increased device wear, this invention employs a dual anti-vibration logic of dynamic hysteresis interval and operating condition delay determination. The hysteresis interval width can be dynamically adjusted according to the ship's operating conditions. In highly dynamic, heavy-load operation conditions, the hysteresis interval is widened to prevent erroneous start-ups and shutdowns caused by small temperature fluctuations. In steady-state berthing and cruising conditions, the hysteresis interval is narrowed to ensure temperature control accuracy.

[0039] (5) This invention continuously improves the intelligence and adaptability of the system through iterative optimization using machine learning. It has closed-loop self-optimization and upgrade capabilities. By collecting core data such as battery temperature, individual cell temperature difference, and system energy consumption after temperature control in real time, and with high-precision temperature control and low energy consumption as optimization goals, it adopts gradient descent machine learning algorithm to iteratively correct the dynamic threshold model correction coefficient and fuzzy PID control parameters at regular intervals, and continuously optimizes the control logic. At the same time, a dedicated operating condition database for ship battery thermal management is built, which stores the operating parameters and temperature control effect data of different sea conditions and different operating conditions in a structured manner. As the operating time accumulates, the database samples continue to be enriched, and the system can quickly match and adapt the temperature control strategy based on the historical best data. Attached Figure Description

[0040] This manual includes the following figures, which illustrate the following:

[0041] Figure 1 This is a flowchart of a method for intelligent start-stop thermal management of batteries for new energy ships according to the present invention. Detailed Implementation

[0042] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, in order to help those skilled in the art to have a more complete, accurate and in-depth understanding of the inventive concept and technical solution of the present invention, and to facilitate its implementation.

[0043] This invention provides a method for intelligent start-stop thermal management of batteries in new energy ships, comprising the following steps:

[0044] Step 1: Synchronously collect three types of operational data: battery status parameters, ship operating condition parameters, and marine environmental parameters, and transmit them to the main control unit via the ship's CAN bus;

[0045] Step 2: Identify the ship's current operating condition, and based on the battery reference temperature, perform coupled calculations with the collected data to generate dynamic start-stop thresholds for cooling and heating in real time.

[0046] Step 3: Match the differentiated temperature control strategy corresponding to the current operating condition, and generate start-stop control commands and stepless power regulation commands for the thermal management system by combining the dynamic start-stop threshold;

[0047] Step 4: Employ a thermal management method combining liquid cooling and phase change materials to drive the actuators;

[0048] Step 5: Collect battery temperature, individual cell temperature difference and system energy consumption data after temperature control is implemented, compare with the preset optimal temperature control target range, and iteratively correct the calculation parameters of the dynamic start-stop threshold; at the same time, record the temperature control effect under different sea conditions and operating conditions, and build a database of ship battery thermal management operating conditions.

[0049] In step one, the battery status parameters include the highest temperature, lowest temperature, average temperature, temperature rise rate, capacity, charge / discharge rate, internal resistance, and temperature difference between individual cells; the ship operating parameters include navigation status, power load, sailing speed, and battery compartment sealing temperature; and the marine environment parameters include ambient temperature, air humidity, sea wind speed, and seawater temperature.

[0050] In step two, the ship's dynamic load factor is the ratio of the real-time output power of the propulsion motor to its rated power.

[0051] In step two, the formula for calculating the dynamic cooling activation threshold is:

[0052] ;

[0053] The formula for calculating the dynamic cooling shutdown threshold is:

[0054] ;

[0055] in The reference temperature for standard battery cooling is set. The standard cooling shutdown reference temperature for the battery. For the real-time temperature rise rate of the battery, For ship dynamic load factor, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, load correction factor, and environmental correction factor, respectively.

[0056] In step two, the formula for calculating the dynamic heating activation threshold is:

[0057] ;

[0058] The formula for calculating the dynamic heating shut-off threshold is:

[0059] ;

[0060] in Set the reference temperature for standard battery heating. The standard heating shut-off reference temperature for the battery is [temperature value missing]. For the real-time temperature rise rate of the battery, For battery power, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, battery charge correction factor, and environmental correction factor, respectively.

[0061] In step two, the operating conditions are divided into four categories: parking and standby, low-speed cruising, heavy-load operation, and extreme temperature range; the corresponding differentiated temperature control strategy in step three is as follows:

[0062] In standby mode, the cooling activation threshold is raised and the heating trigger sensitivity is reduced. Low-power liquid cooling cycle is only activated for temperature control when the battery temperature fluctuates abnormally or the temperature difference between individual cells exceeds the standard.

[0063] Under low-speed cruising conditions, the liquid cooling flow rate and fan speed are dynamically and finely adjusted to control the thermal management system to operate within a preset rated power range and maintain stable battery temperature.

[0064] Under heavy-load operating conditions, the cooling activation threshold is reduced, and the liquid cooling cycle power is increased to the preset value of the rated power. In conjunction with phase change materials, the accumulated heat of the battery is absorbed, and the maximum temperature of the battery and the temperature difference between individual cells are controlled.

[0065] Under extreme temperature conditions, the cooling system is activated in advance in high-temperature marine environments to suppress heat accumulation, while a low-heat-consumption heating mode is adopted in low-temperature marine environments, and the heating time and power are dynamically adjusted according to the battery charge.

[0066] In step three, a fuzzy PID adaptive control algorithm is used to generate stepless power regulation commands. The average battery temperature, maximum temperature difference of individual cells, and temperature rise rate are used as inputs. The proportional, integral, and derivative parameters of the PID controller are corrected in real time through preset fuzzy rules to regulate the start-up and shutdown timing and operating power of the thermal management system.

[0067] Step three also includes intelligent anti-start-stop oscillation processing: setting dynamic start-stop hysteresis interval and operating condition delay judgment logic; the width of the dynamic start-stop hysteresis interval is adjusted in real time according to the current operating condition, widening the hysteresis interval under high dynamic operating conditions and narrowing the hysteresis interval under steady-state operating conditions; the operating condition delay judgment logic is that the start-stop command is triggered only when the battery temperature reaches the corresponding start-stop threshold and the duration meets the preset conditions.

[0068] In step four, the actuators include a liquid-cooled circulating pump, a variable frequency cooling fan, a PTC heating module, and a flow regulating valve; phase change material is laid in the gaps between battery modules and at the bottom of the modules.

[0069] In step five, machine learning algorithms are used to iteratively correct the calculation parameters of the dynamic start-stop threshold, and the temperature control strategy under different sea conditions and operating conditions is continuously updated based on the ship battery thermal management operating condition database.

[0070] The present invention will now be described in detail.

[0071] The system synchronously collects three types of parameters: battery status, ship operating conditions, and marine environment. All parameters are sampled at a uniform frequency of 100ms. Data is aggregated and transmitted to the main control unit via the ship's CAN bus, with end-to-end transmission latency controlled within 20ms to ensure data synchronization and real-time performance. Battery status parameters, including the highest, lowest, and average temperatures of individual battery cells, as well as the temperature difference between cells, are collected by NTC temperature sensors located on the surface of each battery cell. The temperature rise rate is calculated by the main control unit using a unit-time difference calculation of the average temperature. Battery state of charge (SOC), charge / discharge rate, and DC internal resistance are calculated and output in real time by the battery BMS and uploaded via the BMS's dedicated CAN interface.

[0072] Ship operating parameters are collected, including navigation status and speed data, which are directly read from the ship's power control system bus. The power load factor is calculated in real time by the main control unit. The calculation method is as follows: the ship's power load factor is determined by the ratio of the real-time output power of the propulsion motor to the rated power of the propulsion motor. The larger the value, the higher the ship's power load. The sealed temperature of the battery compartment is obtained by taking the arithmetic mean of the temperature sensors arranged at the top, middle and bottom of the battery compartment, reflecting the overall thermal state of the compartment environment.

[0073] Marine environmental parameters were collected, including ambient temperature, air humidity, and sea wind speed, which were collected by the ship's onboard weather station; seawater temperature was collected by a platinum resistance temperature sensor located below the waterline on the ship's side, which was used to evaluate the natural heat exchange capacity of the liquid cooling system.

[0074] Operating condition identification and dynamic start-stop threshold calculation are the core decision-making steps of this invention. First, the current operating condition is identified based on collected data. Then, using the battery reference temperature as a basis, and combining multi-parameter coupling calculations, two sets of dynamic start-stop thresholds for cooling and heating are generated in real time, replacing the traditional fixed thresholds. The main control unit classifies the ship's operating status into four typical operating conditions based on three dimensions: sailing speed, power load coefficient, and ambient temperature. The judgment rules are as follows:

[0075] Parking and standby conditions: sailing speed is 0 and dynamic load factor L < 0.1;

[0076] Low-speed cruise condition: The sailing speed is 3~8 knots and the power load factor L is 0.1~0.4;

[0077] Heavy-load operation conditions: sailing speed > 8 knots, or dynamic load factor L > 0.6;

[0078] Extreme temperature conditions: marine ambient temperature > 40℃ (high temperature extreme), or marine ambient temperature < 0℃ (low temperature extreme).

[0079] The dynamic start / stop threshold model for cooling systems uses cooling thresholds for active cooling loops such as liquid cooling cycles and cooling fans to determine when the cooling system should be turned on and off. The threshold is based on a reference temperature, with adjustments for temperature rise rate, dynamic load, and ambient temperature, and is updated dynamically in real time. The formula for calculating the dynamic cooling start threshold is:

[0080] ;

[0081] The formula for calculating the dynamic cooling shutdown threshold is:

[0082] ;

[0083] in The reference temperature for standard battery cooling is set. The standard cooling shutdown reference temperature for the battery. For the real-time temperature rise rate of the battery, For ship dynamic load factor, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, load correction factor, and environmental correction factor, respectively.

[0084] The formula for calculating the dynamic heating shut-off threshold is:

[0085] ;

[0086] The formula for calculating the dynamic heating shut-off threshold is:

[0087] ;

[0088] in Set the reference temperature for standard battery heating. The standard heating shut-off reference temperature for the battery is [temperature value missing]. For the real-time temperature rise rate of the battery, For battery power, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, battery charge correction factor, and environmental correction factor, respectively.

[0089] The logic behind the correction coefficients is explained as follows: the faster the battery cools down (the larger the negative and absolute value of the temperature rise rate), the higher the heating start threshold, allowing heating to start earlier and suppressing rapid temperature drops; the higher the battery SOC, the higher the heating start / stop threshold, allowing sufficient heating to ensure battery performance; the lower the SOC, the lower the threshold, reducing heating time and power, prioritizing the ship's power and range; the lower the ambient temperature, the higher the heating start threshold, compensating for environmental heat dissipation in advance; the higher the ambient temperature, the lower the threshold, reducing ineffective heating.

[0090] Based on the identified operating conditions and calculated dynamic thresholds, a differentiated temperature control strategy is matched, and a fuzzy PID algorithm is used to generate start / stop commands and stepless power adjustment commands. At the same time, an anti-vibration mechanism is used to filter out false triggers.

[0091] To achieve precise temperature control in various scenarios, corresponding control logic is matched to four types of operating conditions.

[0092] Parking standby mode: Based on the dynamic threshold, the cooling activation threshold is further increased by 2℃ and the heating trigger sensitivity is reduced. Under normal conditions, the thermal management system is in standby hibernation. Only when the temperature difference of a single battery cell exceeds 5℃ or an abnormal temperature rise occurs will a low-power liquid cooling small-flow circulation of 10% of the rated power be started for temperature equalization and control, eliminating ineffective energy consumption.

[0093] Low-speed cruise mode: adopts mild control mode, dynamically fine-tunes liquid cooling flow and fan speed, controls the thermal management system to operate in the range of 20%~40% of rated power, maintains the battery temperature in the optimal range of 32~34℃, avoids frequent system start-stop, and balances temperature control effect and energy consumption.

[0094] Heavy-duty operation conditions: Based on the dynamic threshold, the cooling activation threshold is further reduced by 1℃, and the liquid cooling circulation power is increased to 80%~100% of the rated power. In conjunction with phase change materials, the accumulated heat of the battery is quickly absorbed. At the same time, the opening of the flow regulating valve of each branch is adjusted to enhance the cooling of the high-temperature module, and the maximum battery temperature is strictly controlled to not exceed 40℃ and the temperature difference between individual cells is not more than 5℃.

[0095] Extreme temperature conditions: In high-temperature marine environments, the cooling system is activated in advance and the heat exchange power is increased to enhance heat dissipation by utilizing the low-temperature characteristics of seawater and suppress heat accumulation; in low-temperature marine environments, a low-heat-consumption heating mode is adopted. When SOC > 50%, full-power rapid heating is allowed, and when SOC < 30%, the upper limit of heating power is limited to 30% of the rated power. The heating time and power are dynamically adjusted according to SOC to avoid excessive power consumption during low-temperature heating.

[0096] A fuzzy PID adaptive control algorithm is employed to generate stepless power regulation commands, replacing traditional fixed-parameter PID and on / off control, thus adapting to the fluctuating operating conditions of ships. The inputs to the PID algorithm are: the deviation between the average battery temperature and the target temperature, the maximum temperature difference between individual cells, and the real-time temperature rise rate of the battery; the outputs are: the proportional coefficient correction, integral coefficient correction, and derivative coefficient correction of the PID controller. Fuzzy inference is performed using the Mamdani inference method, and precise parameter corrections are obtained through centroid defuzzification, updating the PID controller parameters in real time.

[0097] The intelligent anti-start-stop oscillation mechanism addresses the frequent start-stop issues caused by marine environmental fluctuations and data noise. It employs an anti-oscillation mechanism that adds a hysteresis width to the dynamic start-stop threshold. Under high-dynamic conditions (heavy load operation, variable speed navigation), the hysteresis width is set to 3°C to widen the start-stop threshold interval and prevent frequent start-stops triggered by small temperature fluctuations. Under steady-state conditions (stationary standby, constant speed cruising), the hysteresis width is set to 1°C to ensure temperature control accuracy. A delay timer is set to issue a cooling start command only when the battery temperature is consistently above the cooling start threshold for ≥2 seconds; and a cooling stop command only when the battery temperature is consistently below the cooling stop threshold for ≥3 seconds. The heating circuit delay rule is consistent with the cooling rule to filter out instantaneous data fluctuations and sensor measurement errors, thus avoiding accidental start-stops.

[0098] The composite thermal management execution control step is based on control commands, using a composite architecture of liquid cooling and phase change materials to perform temperature control actions, achieving a synergistic effect of active and precise regulation and passive temperature equalization assistance. The variable frequency liquid-cooled circulating pump can independently adjust the coolant flow rate of each battery module branch; the rated airflow and speed of the variable frequency cooling fan are continuously adjustable; the PTC heating module supports stepless power adjustment. All components can quickly adapt to changes in battery thermal load.

[0099] The passive phase change temperature homogenizing material uses a paraffin-based composite phase change material, which is laid in the gaps between battery modules and at the bottom of the modules. When the battery temperature rises to the phase change temperature, the material absorbs heat through melting and stores heat, thus smoothing out temperature peaks; when the battery temperature drops, the material releases heat through solidification and releases heat, maintaining temperature stability and achieving passive temperature homogenization, which helps reduce the load and start-stop frequency of the active system.

[0100] Real-time data collection of the battery's average temperature, maximum temperature difference between individual cells, and total energy consumption of the thermal management system (power integral values ​​of liquid cooling pump, fan, and PTC) after temperature control execution is used as the basis for performance evaluation.

[0101] With temperature control accuracy as the priority and energy consumption optimization as a secondary goal, the gradient descent machine learning algorithm is used to compare the actual temperature control effect with the preset optimal target range (battery temperature 25~35℃, single cell temperature difference ≤5℃, and lowest energy consumption) every hour of operation. The correction coefficients of the dynamic threshold model and the fuzzy PID parameters are then iteratively corrected to continuously improve the temperature control accuracy.

[0102] The system stores each run's data in a structured format, categorized by operating condition type, environmental parameters, battery status, control parameters, and temperature control effectiveness, into a local operating condition database. As the ship's operating time increases, the database is continuously enriched, allowing the system to quickly match optimal control parameters by calling upon historical data, thus continuously improving its adaptability to different sea states and operating conditions.

[0103] The beneficial effects of the present invention are described in detail below.

[0104] This invention features multi-parameter coupled dynamic threshold control and high temperature control accuracy. Unlike the traditional coarse control mode of fixed start-stop thresholds for marine battery thermal management, this invention is based on three types of real-time operating data: battery state parameters, ship operating condition parameters, and marine environment parameters. Through coupled calculations of multi-dimensional parameters such as temperature rise rate, power load, ambient temperature, and battery SOC, it constructs a dedicated dynamic cooling and heating start-stop threshold model, which can update threshold parameters in real time according to the ship's operating status and the marine environment. This effectively solves the problems of traditional fixed threshold control being unable to adapt to complex marine conditions, lagging temperature control, and poor individual cell consistency, significantly improving the temperature control accuracy of marine batteries across all scenarios.

[0105] This invention significantly improves the adaptability of ship batteries to different operating conditions, covering a wide range of scenarios. It precisely divides shipboard operations into four core operating conditions: berthing and standby, low-speed cruising, heavy-load operation, and extreme temperature ranges. For each condition, it matches a customized temperature control strategy based on the battery's thermal load characteristics and navigation requirements. It comprehensively covers scenarios for normal navigation, operation, berthing, and extreme sea environments, solving the problems of traditional thermal management systems' single control logic, inability to adapt to dynamic changes in ship operating conditions, and temperature control failure in extreme sea conditions. Its adaptability far surpasses traditional general-purpose temperature control solutions.

[0106] This invention achieves excellent temperature control and energy consumption balance by employing a composite thermal management architecture that combines active liquid cooling temperature control with passive phase change temperature homogenization. On the active side, a variable-frequency liquid-cooled pump, a variable-speed fan, and a stepless power PTC heating module enable precise and rapid active temperature control intervention, allowing for targeted adjustment of flow rates in each battery module branch to accurately control the temperature of high-temperature modules. On the passive side, paraffin-based phase change material laid between and at the bottom of the battery modules utilizes the properties of melting heat absorption and solidification heat release to smooth battery temperature peaks, reduce temperature fluctuations, and optimize module temperature homogenization. This significantly reduces the overall energy consumption of the thermal management system, achieving a two-way balance between high-precision temperature control and low-energy operation, thus meeting the core requirements of energy-saving navigation in ships.

[0107] This invention features an intelligent anti-vibration mechanism, ensuring high system stability. Addressing the challenges posed by complex marine environments, wind and wave interference, sensor data noise, and frequent fluctuations in operating conditions that can lead to frequent start-ups and shutdowns of the thermal management system, temperature control oscillations, and increased component wear, this invention employs a dual anti-vibration logic of dynamic hysteresis interval and operating condition delay determination. The hysteresis interval width can be dynamically adjusted according to the ship's operating conditions. During highly dynamic, heavy-load operations, the hysteresis interval is widened to prevent erroneous start-ups and shutdowns caused by small temperature fluctuations. During steady-state berthing and cruising operations, the hysteresis interval is narrowed to ensure temperature control accuracy.

[0108] This invention utilizes machine learning for iterative optimization, continuously improving the system's intelligence and adaptability. It possesses closed-loop self-optimization and upgrade capabilities. By collecting core data such as battery temperature, individual cell temperature difference, and system energy consumption in real time after temperature control, and aiming for high-precision temperature control and low energy consumption, it employs a gradient descent machine learning algorithm to iteratively correct the dynamic threshold model correction coefficients and fuzzy PID control parameters at regular intervals, continuously optimizing the control logic. Simultaneously, a dedicated operating condition database for ship battery thermal management is established, structurally storing operating parameters and temperature control effect data under different sea conditions and operating conditions. As operating time accumulates, the database samples continuously enrich, allowing the system to quickly match suitable temperature control strategies based on historical optimal data.

[0109] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution; or the direct application of the inventive concept and technical solution to other situations without modification, are all within the protection scope of the present invention.

Claims

1. A method for intelligent start-stop thermal management of batteries for new energy ships, characterized in that, Includes the following steps: Step 1: Synchronously collect three types of operational data: battery status parameters, ship operating condition parameters, and marine environmental parameters; Step 2: Identify the ship's current operating condition, and based on the battery reference temperature, perform coupled calculations with the collected data to generate dynamic start-stop thresholds for cooling and heating in real time. Step 3: Match the differentiated temperature control strategy corresponding to the current operating condition, and generate start-stop control commands and stepless power regulation commands for the thermal management system by combining the dynamic start-stop threshold; Step 4: Employ a thermal management method combining liquid cooling and phase change materials to drive the actuators; Step 5: Collect battery temperature, individual cell temperature difference and system energy consumption data after temperature control is implemented, compare with the preset optimal temperature control target range, and iteratively correct the calculation parameters of the dynamic start-stop threshold; at the same time, record the temperature control effect under different sea conditions and operating conditions, and build a database of ship battery thermal management operating conditions.

2. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step one, the battery status parameters include the highest temperature, lowest temperature, average temperature, temperature rise rate, capacity, charge / discharge rate, internal resistance, and temperature difference between individual cells; the ship operating parameters include navigation status, power load, sailing speed, and battery compartment sealing temperature; and the marine environment parameters include ambient temperature, air humidity, sea wind speed, and seawater temperature.

3. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step two, the ship's dynamic load factor is the ratio of the real-time output power of the propulsion motor to its rated power.

4. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step two, the formula for calculating the dynamic cooling activation threshold is: ； The formula for calculating the dynamic cooling shutdown threshold is: ； in The reference temperature for standard battery cooling is set. The standard cooling shutdown reference temperature for the battery. For the real-time temperature rise rate of the battery, For ship dynamic load factor, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, load correction factor, and environmental correction factor, respectively.

5. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step two, the formula for calculating the dynamic heating activation threshold is: ； The formula for calculating the dynamic heating shut-off threshold is: ； in Set the reference temperature for standard battery heating. The standard heating shut-off reference temperature for the battery is [temperature value missing]. For the real-time temperature rise rate of the battery, For battery power, Let K be the marine ambient temperature, and k1, k2, and k3 be the temperature rise correction factor, battery charge correction factor, and environmental correction factor, respectively.

6. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step two, the operating conditions are divided into four categories: parking and standby, low-speed cruising, heavy-load operation, and extreme temperature range; the corresponding differentiated temperature control strategy in step three is as follows: In standby mode, the cooling activation threshold is raised and the heating trigger sensitivity is reduced. Low-power liquid cooling cycle is only activated for temperature control when the battery temperature fluctuates abnormally or the temperature difference between individual cells exceeds the standard. Under low-speed cruising conditions, the liquid cooling flow rate and fan speed are dynamically and finely adjusted to control the thermal management system to operate within a preset rated power range and maintain stable battery temperature. Under heavy-load operating conditions, the cooling activation threshold is reduced, and the liquid cooling cycle power is increased to the preset value of the rated power. In conjunction with phase change materials, the accumulated heat of the battery is absorbed, and the maximum temperature of the battery and the temperature difference between individual cells are controlled. Under extreme temperature conditions, the cooling system is activated in advance in high-temperature marine environments to suppress heat accumulation, while a low-heat-consumption heating mode is adopted in low-temperature marine environments, and the heating time and power are dynamically adjusted according to the battery charge.

7. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step three, a fuzzy PID adaptive control algorithm is used to generate stepless power regulation commands. The average battery temperature, maximum temperature difference of individual cells, and temperature rise rate are used as inputs. The proportional, integral, and derivative parameters of the PID controller are corrected in real time through preset fuzzy rules to regulate the start-up and shutdown timing and operating power of the thermal management system.

8. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: Step three also includes intelligent anti-start-stop oscillation processing: setting dynamic start-stop hysteresis interval and operating condition delay judgment logic; the width of the dynamic start-stop hysteresis interval is adjusted in real time according to the current operating condition, widening the hysteresis interval under high dynamic operating conditions and narrowing the hysteresis interval under steady-state operating conditions; the operating condition delay judgment logic is that the start-stop command is triggered only when the battery temperature reaches the corresponding start-stop threshold and the duration meets the preset conditions.

9. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step four, the actuators include a liquid-cooled circulating pump, a variable frequency cooling fan, a PTC heating module, and a flow regulating valve; phase change material is laid in the gaps between battery modules and at the bottom of the modules.

10. The method for intelligent start-stop thermal management of new energy ship batteries as described in claim 1, characterized in that: In step five, machine learning algorithms are used to iteratively correct the calculation parameters of the dynamic start-stop threshold, and the temperature control strategy under various sea states and operating conditions is continuously updated based on the ship battery thermal management operating condition database.

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