Thermal guarantee control method and system for power battery of hybrid power locomotive

Abstract

The invention discloses a hybrid locomotive power battery thermal guarantee control method and system, and the method comprises the steps: a control unit is configured to obtain first working condition data of an internal combustion engine, and generates a predicted preheating generation amount according to the first working condition data; acquiring second working condition data of the power battery system, and generating predicted power battery system consumption according to the second working condition data; generating a control instruction according to the predicted preheating generation amount and the predicted power battery system consumption, wherein the control instruction is used for determining the output heat of the waste heat recovery unit and the output heat or storage heat of the heat storage unit; the waste heat recovery unit is integrally arranged on an exhaust manifold of the internal combustion engine and makes contact with a cooling circulation pipeline of the power battery system and the heat storage unit. The heat storage unit is further in contact with the cooling circulation pipeline.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of engine system technology, and in particular to a method and system for thermal protection control of power battery in hybrid locomotives. Background Technology

[0002] Hybrid locomotives, as an important direction for the green transformation of the rail transit sector, have attracted much attention in their research and application. These locomotives typically employ a hybrid power mode where the power battery system and diesel engine system work together to achieve energy conservation and emission reduction goals. However, a long-standing and serious technical bottleneck has hindered their widespread adoption and reliable operation in high-altitude and cold regions: the severe performance degradation of the power battery system in low-temperature environments.

[0003] Currently, the main technical solution used in the thermal management of locomotive power batteries is the resistance direct heating scheme, which has the following drawbacks: extremely unreasonable energy utilization and low overall energy efficiency; slow heating response and poor thermal management performance; and inability to cope with the drastic fluctuations in internal combustion engine power and waste heat output. Summary of the Invention

[0004] This invention provides a method and system for thermal protection control of power batteries in hybrid locomotives, aiming to solve at least one defect in the prior art.

[0005] In a first aspect, embodiments of the present invention provide a method for thermal protection control of a power battery in a hybrid locomotive, comprising:

[0006] The control unit is configured to acquire first operating condition data of the internal combustion engine and generate a predicted preheating amount based on the first operating condition data; acquire second operating condition data of the power battery system and generate a predicted power battery system consumption amount based on the second operating condition data;

[0007] Control commands are generated based on the predicted preheating amount and the predicted power battery system consumption. The control commands are used to determine the output heat of the waste heat recovery unit and the output heat or stored heat of the heat storage unit.

[0008] The waste heat recovery unit is integrated on the exhaust manifold of the internal combustion engine. The waste heat recovery unit is in contact with the cooling circulation pipeline of the power battery system and the heat storage unit. The heat storage unit is also in contact with the cooling circulation pipeline.

[0009] Optionally, generating the control commands includes:

[0010] Based on the predicted preheating generation and the predicted power battery system consumption at the current moment, a control sequence within a preset time window is generated. The control sequence includes several control instructions, which are used to determine the opening degree of the first valve of the waste heat recovery unit and the opening degree of the second valve of the heat storage unit at the corresponding moment.

[0011] The opening degree of the first valve is used to control the output heat of the waste heat recovery unit, and the opening degree of the second valve is used to control the output heat or stored heat of the heat storage unit.

[0012] Optionally, the control command is also used to determine the pump speed of the cooling circulation pipeline at a corresponding time, and the pump speed is used for coolant flow control of the cooling circulation pipeline.

[0013] Optionally, generating the control sequence includes:

[0014] Acquire environmental data, determine environmental compensation amount based on the environmental data, and generate control commands based on the predicted preheating generation amount, the predicted power battery system consumption amount, and the environmental compensation amount;

[0015] The environmental data includes at least atmospheric pressure and oxygen content.

[0016] Secondly, embodiments of the present invention also provide a hybrid electric vehicle power battery system, comprising:

[0017] Control unit, waste heat recovery unit, and heat storage unit;

[0018] The waste heat recovery unit is integrated into the exhaust manifold of the internal combustion engine, and the waste heat recovery unit is in contact with the cooling circulation pipeline of the power battery system and the heat storage unit respectively.

[0019] The heat storage unit is also configured to contact the cooling circulation pipeline;

[0020] The control unit is configured to acquire first operating condition data of the internal combustion engine and generate a predicted preheating amount based on the first operating condition data; acquire second operating condition data of the power battery system and generate a predicted power battery system consumption amount based on the second operating condition data;

[0021] Control commands are generated based on the predicted preheating amount and the predicted power battery system consumption. The control commands are used to determine the output heat of the waste heat recovery unit and the output heat or stored heat of the heat storage unit.

[0022] Optionally, the coolant in the cooling circulation pipeline is a nanofluid, which includes a base fluid, nanoparticles, and a dispersant.

[0023] Optionally, the waste heat recovery unit is also equipped with an automatic cleaning device for cleaning the heat exchanger in the waste heat recovery unit.

[0024] Optionally, the waste heat recovery unit includes at least two heat exchangers, with multiple heat exchangers connected in series, and a bypass valve is provided between two heat exchangers.

[0025] Optionally, the waste heat recovery unit includes a main heat exchanger module, an auxiliary heat exchanger module, and a supplementary heat exchanger module;

[0026] The main heat exchanger module, auxiliary heat exchanger module, and supplementary heat exchanger module are connected by a controllable valve; the design temperatures of the main heat exchanger module, auxiliary heat exchanger module, and supplementary heat exchanger module decrease sequentially.

[0027] Optionally, the thermal storage unit includes a phase change material, the phase change temperature of which is 55–65°C.

[0028] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention proposes a control method in which, by acquiring real-time data on the first operating condition of the internal combustion engine (such as speed, load, and exhaust temperature) and the second operating condition of the power battery (such as SOC value, charging and discharging current, and current temperature), the predicted preheating generation and the predicted power battery system consumption can be dynamically updated. Based on this, control commands are adjusted in real time, overcoming the limitations of traditional passive thermal management and achieving bidirectional prediction of waste heat supply and battery thermal demand. Control commands generated based on the bidirectional prediction results can pre-schedule the output heat of the waste heat recovery unit and the stored heat of the heat storage unit, avoiding thermal management lag caused by sudden changes in heat demand or supply. Simultaneously, it can avoid temperature fluctuations caused by ad-hoc decisions and address the problem of drastic fluctuations in internal combustion engine power and waste heat production. Attached Figure Description

[0029] Figure 1 This is a flowchart of the control method in the embodiment;

[0030] Figure 2 This is a block diagram of the hybrid locomotive power battery system in the embodiment;

[0031] Figure 3 This is a flowchart illustrating the operation of the hybrid locomotive power battery system in the embodiment. Detailed Implementation

[0032] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0033] Example 1

[0034] Figure 1 This is a flowchart of the control method in the embodiment, for reference. Figure 1 The control methods include:

[0035] S101. The control unit is configured to acquire first operating condition data of the internal combustion engine, generate a predicted preheating amount based on the first operating condition data, acquire second operating condition data of the power battery system, and generate a predicted power battery system consumption amount based on the second operating condition data.

[0036] S102. Generate control instructions based on the predicted preheating generation and the predicted power battery system consumption. The control instructions are used to determine the output heat of the waste heat recovery unit and the output heat or stored heat of the heat storage unit.

[0037] In this scheme, the power battery system of the hybrid locomotive is defined as including a control unit, a waste heat recovery unit, and a heat storage unit.

[0038] The waste heat recovery unit is integrated into the exhaust manifold of the internal combustion engine. The waste heat recovery unit is in contact with the cooling circulation pipeline and the heat storage unit of the power battery system. The heat storage unit is also in contact with the cooling circulation pipeline.

[0039] In this scheme, the internal combustion engine (system) serves as one of the main power sources of the locomotive, and is also the source of high-temperature exhaust heat in the embodiments of this invention.

[0040] In this scheme, the power battery system serves as the auxiliary power source and energy storage unit for the locomotive, and is also the target object for thermal management in this method.

[0041] In this solution, the waste heat recovery unit serves as a key front-end component for efficient energy capture. It is used to achieve heat exchange with the high-temperature waste gas, thereby preheating and recovering the waste gas. The heat recovery efficiency of the preheating recovery device is set to be stable above 70%, with an operating temperature exceeding 500℃ and a pressure resistance exceeding 0.5MPa.

[0042] In this scheme, the cooling circulation pipeline is used to realize energy transfer between the power battery system. The cooling circulation pipeline stores coolant, and the power battery can be heated or cooled through thermal interaction between the coolant and the power battery.

[0043] In this solution, the heat storage unit is used to store excess heat when the internal combustion engine is running at high power and the waste heat output far exceeds the immediate needs of the battery; when the internal combustion engine is idling, stopped, or the waste heat is insufficient, it releases the stored heat to continuously heat the battery system, ensuring the continuity and stability of heat supply.

[0044] In this solution, the control unit may include a high-performance multi-core microprocessor that meets automotive-grade standards. The control unit may be equipped with a high-precision temperature, pressure, and flow sensor array, and through a CAN bus network and a high-speed Ethernet interface, it can achieve full-duplex, real-time data interaction with systems such as the Train Control and Management System (TCMS), Engine Control Unit (ECU), and Battery Management System (BMS).

[0045] In this solution, the control unit can collect specified data as needed, including but not limited to: real-time speed, output torque, fuel injection quantity, and exhaust temperature of the internal combustion engine; temperature, total voltage, total current, and SOC status of various points of the power battery pack; and multi-source and heterogeneous operating parameters such as coolant temperature, pump speed, and valve opening.

[0046] For example, in step S101, by collecting real-time operating data of the internal combustion engine and the power battery, the waste heat supply and battery heat consumption in the future period are predicted respectively, providing a quantitative basis for subsequent decision-making.

[0047] For example, in this solution, the control unit can collect the first operating condition data of the internal combustion engine from the engine control system (ECU) in real time via CAN bus / high-speed Ethernet, including but not limited to: real-time internal combustion engine speed, output torque, fuel injection quantity, and exhaust temperature.

[0048] The control unit can be configured to predict the amount (unit: kJ) and quality (i.e. waste heat temperature, which directly affects heat exchange efficiency) of waste heat generated in the future within a certain period of time, based on a preset internal combustion engine waste heat model (which can be trained through a large amount of experimental data and establishes a mapping relationship between speed / torque / fuel injection quantity and total waste heat).

[0049] For example, in this solution, the control unit can be configured to interact with the battery management system (BMS) to collect second operating condition data of the power battery, including: temperature at various points of the power battery pack, total voltage, total current, and SOC (State of Charge); at the same time, it can obtain future load demand instructions (such as whether the locomotive needs high-power traction, whether to enter charging mode, etc.) from the locomotive central control system (TCMS).

[0050] The control unit can be configured to predict the battery's heat consumption over a future period based on a preset battery thermal demand model (which relates to the battery's chemical characteristics and establishes the relationship between the current temperature / SOC / load demand and the heat required to maintain the target temperature).

[0051] For example, in step S102, based on the predicted preheating generation and predicted power battery system consumption output in step S101, control commands are generated through forward optimization calculations to determine the output heat distribution of the waste heat recovery unit and the heat storage / heat release status of the heat storage unit, thereby achieving precise scheduling of heat flow.

[0052] For example, in this solution, the specific form of the internal combustion engine waste heat model is not limited; for instance, its form can be:

[0053] Qy=(w1×x1+w2×x2+…w i ×x i )×(T p -T h )×K

[0054] In the formula, Qy represents the predicted preheating amount, x1~x i This indicates the selected parameters (such as engine speed, torque, fuel injection quantity, etc.), w1~w i T represents the corresponding weight. p T represents the exhaust temperature. h The value represents the ambient temperature, and K represents the coefficient.

[0055] For example, in this solution, the specific form of the battery thermal demand model is not limited; for instance, its form can be:

[0056] Qs=B1×B2×(T t -T r )-Qd

[0057] In the formula, Qs represents the predicted power battery system consumption, B1 represents the battery mass, B2 represents the specific heat capacity, and T... t T represents the target temperature. r Qd represents the current temperature, and Qd represents the heat generated during battery discharge.

[0058] In this scheme, based on the principle that the system's energy efficiency maximization objective function can be solved, control commands can be generated. The specific decision logic corresponding to the control commands can be as follows:

[0059] If Qy≥Qs+remaining capacity of the thermal storage unit, then 30% to 70% of the heat energy in the waste heat recovery unit will exchange heat with the cooling circulation pipeline, and the thermal storage unit will absorb the excess waste heat.

[0060] If Qy≈Qs (deviation≤10%), then 100% of the heat energy in the waste heat recovery unit enters the cooling circulation pipeline, and the heat storage unit is on standby.

[0061] If Qy < Qs or Qy = 0, the waste heat recovery unit does not participate in heat exchange, and the heat storage unit releases heat to provide the thermal energy required by the power battery.

[0062] This embodiment proposes a control method that dynamically updates the predicted preheating generation and power battery system consumption by acquiring real-time data on the first operating condition of the internal combustion engine (such as engine speed, load, and exhaust temperature) and the second operating condition of the power battery (such as SOC value, charging and discharging current, and current temperature). Based on this, control commands are adjusted in real time, overcoming the limitations of traditional passive thermal management and achieving bidirectional prediction of waste heat supply and battery heat demand. Control commands generated based on the bidirectional prediction results can pre-schedule the output heat of the waste heat recovery unit and the stored heat of the heat storage unit, avoiding thermal management lag caused by sudden changes in heat demand or supply. It also avoids temperature fluctuations caused by ad-hoc decisions and can address the problem of drastic fluctuations in internal combustion engine power and waste heat production.

[0063] Based on any of the aforementioned solutions, in one possible implementation, generating control instructions includes:

[0064] Based on the predicted preheating generation and the predicted power battery system consumption at the current moment, a control sequence is generated within a preset time window. The control sequence includes several control instructions, which are used to determine the opening degree of the first valve of the waste heat recovery unit and the opening degree of the second valve of the heat storage unit at the corresponding moment.

[0065] In this scheme, the opening degree of the first valve is used to control the output heat of the waste heat recovery unit, and the opening degree of the second valve is used to control the output heat or stored heat of the heat storage unit.

[0066] In this scheme, the control sequence refers to a set of continuous control commands generated at fixed time intervals within the time window predicted by S101. Each control command contains two core parameters: the first valve opening degree and the second valve opening degree.

[0067] First valve opening: The opening degree of the flow control valve of the waste heat recovery unit (0~100%) directly determines the amount of heat recovered from the exhaust manifold of the internal combustion engine per unit time (the larger the opening degree, the greater the coolant flow rate and the more heat recovered).

[0068] The second valve opening: corresponds to the opening of the bidirectional control valve of the thermal storage unit (-100% to +100%). Among them, the positive opening (0 to 100%) indicates the thermal storage mode, and the larger the opening, the higher the proportion of heat flowing to the thermal storage unit; the negative opening (-100% to 0) indicates the heat release mode, and the larger the absolute value, the more heat is released by the thermal storage unit; the opening of 0 indicates that the thermal storage unit is in standby mode.

[0069] For example, in this solution, the optimal control sequence can be solved using dynamic programming mathematical methods to ensure that the actions of the waste heat recovery and heat storage units can accurately match the battery thermal demand within a preset time window.

[0070] For example, in this scheme, the generation of the control sequence is set with the highest overall system energy efficiency as the core objective. By constructing a mathematical objective function, it is ensured that the deviation between waste heat supply and battery heat demand is minimized throughout the entire time window, while also meeting the physical constraints of hardware operation.

[0071] To ensure the feasibility of the control sequence, the objective function must satisfy three types of physical constraints: The first is the valve opening constraint, where the opening of the first valve of the waste heat recovery unit must be between 0% and 100%. The second is the dynamic balance constraint of the heat storage unit, where the heat storage unit's heat storage at each time step must equal the current heat storage plus the heat absorbed by the unit within that step. The third is the heat storage capacity constraint, where the heat storage unit's heat storage at any time step must be between 0 kJ and the maximum heat storage capacity E_max.

[0072] In this scheme, when solving the control sequence using dynamic programming, the optimal decision is found in all possible states at each time point, and finally a complete control sequence is generated.

[0073] For example, in this solution, the Model Predictive Control (MPC) algorithm can also be used to generate the optimal control sequence, thereby achieving the coordinated control requirements of the waste heat recovery unit and the thermal storage unit.

[0074] For example, in this solution, the prediction model used by MPC can be the internal combustion engine waste heat model and the battery thermal demand model in step S101; the optimization time domain of MPC is aligned with the preset time window of the control sequence, and the control time domain is aligned with the control step size to ensure that the control command generated in each step is completely matched with the time node of the control sequence; hardware physical limitations (such as valve opening range, heat storage unit capacity, and coolant flow limit) are transformed into optimization constraints of MPC to avoid the control sequence from exceeding the hardware operating limits.

[0075] In this scheme, when implementing the MPC algorithm, after each control step, actual operating data (such as actual waste heat recovery and battery temperature deviation) is collected by sensors to correct the error of the prediction model and regenerate the control sequence for the next round of optimization in the time domain.

[0076] In this scheme, waste heat management and control are carried out through a control sequence. Compared with using a single command, the control sequence plans the heat flow scheduling in advance for a period of time in the future, avoiding temperature fluctuations caused by ad-hoc decisions.

[0077] Based on any of the aforementioned schemes, in one possible implementation scheme, the control command is also used to determine the pump speed of the cooling circulation pipeline at a corresponding time, and the pump speed is used for coolant flow control of the cooling circulation pipeline.

[0078] In this scheme, the pump speed is set as a parameter of the control command, forming a three-parameter control command (first valve opening, second valve opening, and pump speed). The three parameters work together to achieve precise control of waste heat recovery, ensuring that the coolant flow rate is dynamically matched with the amount of waste heat recovered and the battery heat demand, avoiding heat transfer lag due to insufficient flow rate or energy waste due to excessive flow rate.

[0079] For example, in this scheme, the MPC algorithm can be used to generate a three-parameter control sequence, including:

[0080] The control unit collects real-time data (internal combustion engine operating condition, battery status, flow rate, pressure) every 10 seconds and calls the S101 module to predict the preheating generation amount Q_excess (t) and battery heat demand amount Q_demand (t) for the next 10 seconds (one control cycle).

[0081] Based on Q_surplus(t) and Q_demand(t), the target flow rate Q_target(t) for each cycle is calculated (based on the quantization matching model). Then, the target rotational speed n_target(t) is determined through the rotational speed-flow rate mapping table. Combined with the coordination rules, the target first valve opening V1_target(t) and the target second valve opening V2_target(t) are determined.

[0082] Input the target parameters into the MPC controller, with the goal of minimizing battery temperature deviation and energy consumption, and solve for the optimal control sequence [V1(t),V2(t),n(t)] under the constraints;

[0083] The control unit executes the control command for the current cycle only, and repeats the above steps in the next cycle to continuously optimize and avoid control inaccuracies caused by prediction deviations.

[0084] Based on any of the aforementioned schemes, in one possible implementation, generating the control sequence includes:

[0085] Acquire environmental data, determine environmental compensation based on the environmental data, and generate control commands based on the predicted preheating generation, predicted power battery system consumption, and environmental compensation; the environmental data includes at least ambient atmospheric pressure and ambient oxygen content.

[0086] For example, in this solution, a compensation model can be established based on the influence of atmospheric pressure on the combustion efficiency and waste heat generation of the internal combustion engine:

[0087] With a standard atmospheric pressure of 101.3 kPa as the baseline, the atmospheric pressure compensation coefficient K1 = 1.0. When atmospheric pressure < 101.3 kPa, the combustion efficiency of the internal combustion engine decreases, and the amount of waste heat generated under the same operating conditions decreases. The compensation coefficient K1 = measured atmospheric pressure / 101.3. When atmospheric pressure > 101.3 kPa, the combustion efficiency increases, and the amount of waste heat generated increases. The compensation coefficient K1 = 1.0 + (measured atmospheric pressure - 101.3) / 500.

[0088] Atmospheric pressure compensation ΔQ1: ΔQ1 = predicted preheating generation × (1-K1), used to correct the predicted value of preheating generation.

[0089] For example, in this scheme, a compensation model can be established based on the influence of oxygen content on combustion completeness:

[0090] With a standard oxygen content of 20.9% as the benchmark, the oxygen content compensation coefficient K2 = 1.0. When the oxygen content is < 20.9%, combustion is incomplete, and the amount of waste heat generated is reduced; the compensation coefficient K2 = measured oxygen content / 20.9. When the oxygen content is > 20.9%, combustion is more complete, and the amount of waste heat generated is increased; the compensation coefficient K2 = 1.0 + (measured oxygen content - 20.9) / 200.

[0091] Oxygen content compensation amount ΔQ2: ΔQ2 = predicted preheating generation amount × (1-K2), used for secondary correction of preheating generation amount.

[0092] For example, in this scheme, the comprehensive compensation coefficient K = K1 × K2 is set. The final environmental compensation amount ΔQ = predicted preheating generation amount × (1-K).

[0093] For example, in this scheme, the S101 prediction module is called to obtain the predicted preheating generation amount Q_surplus(i) and the predicted power battery system consumption amount Q_demand(i) for the next control cycle; the corrected preheating generation amount Q'_surplus(i) = Q_surplus(i) × K; the net heat demand Q_net(i) = Q_demand(i) - Q'_surplus(i).

[0094] Based on Q_net(i) and the environmental compensation amount ΔQ, determine the opening degree of the first valve (V1), the opening degree of the second valve (V2), and the pump speed (n):

[0095] When Q_net(i) > 0, V1 = min(100%, 80% + ΔQ × 0.01); V2 = max(-50%, -30% - ΔQ × 0.005); n = min(3000 rpm, 2000 rpm + ΔQ × 5).

[0096] When Q_net(i)≈0, V1=50%+ΔQ×0.005;V2=0%+ΔQ×0.003;n=1500rpm+ΔQ×2.

[0097] When Q_net(i) < 0, V1 = max(30%, 50% - ΔQ × 0.008); V2 = min(60%, 30% + ΔQ × 0.005); n = max(800 rpm, 1500 rpm - ΔQ × 3).

[0098] Example 2

[0099] Figure 2This is a block diagram of the hybrid locomotive power battery system in the embodiment, for reference. Figure 2 The system includes a control unit 100, a waste heat recovery unit 200, and a heat storage unit 300.

[0100] The waste heat recovery unit 200 is integrated on the exhaust manifold of the internal combustion engine. The waste heat recovery unit 200 is in contact with the cooling circulation pipeline of the power battery system and the heat storage unit 300. The heat storage unit 300 is also in contact with the cooling circulation pipeline.

[0101] In this scheme, the waste heat recovery unit 200 is integrated on the exhaust manifold of the internal combustion engine. This approach abandons the traditional idea of ​​adding a heat exchanger at the rear end of the exhaust pipe. The waste heat recovery unit 200 is designed as a vibration-resistant, compact plate heat exchanger directly integrated on the exhaust manifold of the internal combustion engine.

[0102] In this solution, the waste heat recovery unit 200 is made of high-temperature resistant stainless steel (such as 310S or 316L) through precision stamping and vacuum brazing processes. Its flow channel design is optimized by computational fluid dynamics (CFD) to achieve the largest heat exchange area and the highest heat exchange efficiency with high-temperature waste gas while ensuring extremely low flow resistance.

[0103] In this design, flexible connections and mechanical fixing ensure that it can withstand the continuous and severe vibrations and alternating thermal stresses generated during locomotive operation. This design allows the high-grade heat energy in the exhaust gas to be captured to the maximum extent immediately after it leaves the engine. The measured heat recovery efficiency can be stably maintained at over 70%, the operating temperature resistance exceeds 500℃, and the pressure resistance exceeds 0.5MPa.

[0104] This embodiment proposes a system in which the waste heat recovery unit is integrated into the exhaust manifold of the internal combustion engine. This eliminates the need for complex external piping or independent supports for the waste heat recovery function, significantly simplifying the system's spatial layout and reducing the structural load on areas such as the vehicle chassis. Simultaneously, the waste heat recovery unit, heat storage unit, and power battery cooling circulation piping achieve heat transfer through direct contact, reducing heat loss during heat transfer via intermediate media and improving heat transfer efficiency. Integrating the waste heat recovery unit into the core area of ​​the internal combustion engine exhaust manifold—a high-grade waste heat source—maximizes the capture of exhaust waste heat that would otherwise be directly emitted into the environment during engine operation, significantly improving waste heat recovery efficiency.

[0105] In one possible implementation, the heat exchanger in the waste heat recovery unit can be designed as a shell-and-tube heat exchanger, a pin-fin heat exchanger, or a porous material heat exchanger; the heat exchanger is preferably made of 316L stainless steel, 310S stainless steel, INCOREL 625 alloy, or TC4 titanium alloy.

[0106] In one feasible implementation, the waste heat recovery unit is designed with a compact plate heat exchanger made of 316L stainless steel, rigidly connected directly to the diesel engine exhaust manifold outlet via a standard flange. The core dimensions of the heat exchanger are 320mm × 240mm × 85mm, comprising 218 0.4mm thick corrugated stainless steel plates with a herringbone pattern, achieving a total heat exchange area of ​​4.8m². 2 The flow channel design was optimized through computational fluid dynamics simulation, resulting in a pressure drop of only 8.5 kPa under rated operating conditions. The device is designed to operate at a temperature of 650℃ and a pressure of 0.8 MPa.

[0107] In one feasible implementation, the waste heat recovery unit uses a high-temperature resistant, needle-fin, high-efficiency, compact heat exchanger with dimensions of 480mm × 360mm × 180mm. It comprises 286 heat exchange tubes with an outer diameter of 12mm and a wall thickness of 1.2mm. The outer wall of each tube is laser-welded with 316L stainless steel needles, resulting in a total heat exchange area of ​​15.6m². 2 Under rated operating conditions, the exhaust side pressure drop is controlled within 12 kPa, which is 40% lower than that of traditional designs.

[0108] In one feasible implementation, the waste heat recovery unit employs a shell-and-tube heat exchanger made of titanium alloy, installed in the diesel engine exhaust manifold via a flexible corrugated pipe connection. The heat exchanger is designed to measure 450mm × 320mm × 200mm, containing 365 titanium alloy heat exchange tubes with an outer diameter of 10mm and a wall thickness of 1.5mm, arranged in an equilateral triangle, achieving a total heat exchange area of ​​11.8m². 2 The heat exchange tubes are machined with 0.5mm high spiral microfins on their outer wall and coated with HK-60 high-temperature anti-oxidation coating. The design operating pressure is 0.6MPa, and the temperature resistance is 700℃.

[0109] For example, in this solution, the cooling circulation pipeline can be further configured with an intelligent pump control system, which can dynamically adjust the pump's operating status and output power by monitoring the flow, pressure, and temperature parameters of the cooling circulation pipeline in real time.

[0110] For example, in this solution, the cooling circulation pipeline can be further designed with dual or triple pump redundancy to ensure that the standby pump can start immediately in the event of a main pump failure.

[0111] For example, in this solution, the system may be further provided with a thermal insulation layer and insulation material to insulate the high-temperature pipeline and the heat storage unit.

[0112] For example, in this solution, the waste heat recovery unit, heat storage unit, and cooling circulation pipeline can be further equipped with a three-stage filtration device, including a coarse filter, a fine filter, and a magnetic filter.

[0113] In this scheme, the control unit is configured to acquire first operating condition data of the internal combustion engine and generate a predicted preheating amount based on the first operating condition data; acquire second operating condition data of the power battery system and generate a predicted power battery system consumption amount based on the second operating condition data. Control commands are generated based on the predicted preheating amount and the predicted power battery system consumption amount. The control commands are used to determine the output heat of the waste heat recovery unit and the output heat or stored heat of the heat storage unit.

[0114] For example, in this solution, the control unit can be configured to implement any of the control methods described in Embodiment 1. The implementation method and the beneficial effects are the same as the corresponding content described in Embodiment 1, and the specific details will not be described in detail.

[0115] Based on any of the aforementioned schemes, in one possible implementation, the coolant in the cooling circulation pipeline is a nanofluid, which includes a base fluid, nanoparticles, and a dispersant.

[0116] In one possible embodiment, the base fluid of the nanofluid is a 60% (v / v) aqueous solution of ethylene glycol, with 4.0% (w / w) of α-phase alumina nanoparticles surface-modified with KH550 silane coupling agent added. The preparation process employs a two-step method: first, mechanical stirring at 2000 rpm for 120 minutes in a high-speed disperser, followed by ultrasonic treatment at 40 kHz frequency and 800 W power for 240 minutes in an ultrasonic processor. Finally, 0.5% (w / w) of polyvinylpyrrolidone is added as a dispersion stabilizer.

[0117] In one possible implementation, the nanofluid is selected using graphene nanosheets as the reinforcing phase. The graphene nanosheets have the following specifications: 5-8 layers, a sheet diameter of 10-15 μm, and a specific surface area of ​​120-150 m². 2 / g. 2.5% (w / w) of graphene nanosheets were added to a 65% (v / w) aqueous solution of ethylene glycol. The preparation process involved ball milling pretreatment followed by ultrasonic treatment. Finally, 0.8% sodium dodecylbenzenesulfonate was added as a dispersant.

[0118] In one possible embodiment, the base fluid of the nanofluid is a 65% (v / v) aqueous solution of a special high-altitude ethylene glycol (freezing point -55°C), with 3.5% (w / w) hexagonal boron nitride nanosheets (average particle size 200 nm, thickness 5 nm). The preparation process includes: pretreatment for 60 minutes in a three-roll mill with a roller gap of 0.1 mm and a rotation speed of 200 / 600 / 800 rpm, followed by ultrasonic treatment for 180 minutes in an ultrasonic processor at a frequency of 45 kHz and a power of 1000 W. Finally, 0.8% (w / w) of polyvinylpyrrolidone is added as a dispersant and stabilizer.

[0119] In one possible embodiment, the base fluid of the nanofluid is a special low-temperature ethylene glycol mixture composed of 65% ethylene glycol, 30% propylene glycol, and 5% novel antifreeze additive. 4.2% by mass of graphene-coated copper nanocomposite particles are added.

[0120] In one possible embodiment, the base fluid of the nanofluid is a 60% aqueous solution of ethylene glycol, and the nanofluid contains 4.5% silica-coated iron oxide nanoparticles.

[0121] For example, in this solution, antioxidants and corrosion inhibitors can be further added to the coolant to improve the chemical stability of the fluid and its protective performance against metallic materials.

[0122] Based on any of the aforementioned solutions, in one possible implementation, the waste heat recovery unit is further equipped with an automatic cleaning device for cleaning the heat exchanger in the waste heat recovery unit.

[0123] For example, in this solution, the waste heat recovery unit and cooling circulation pipeline can be equipped with an automatic cleaning device to clean the surface of the heat exchanger and the inside of the cooling circulation pipeline (of the waste heat recovery unit) periodically or as needed.

[0124] Based on any of the aforementioned schemes, in one possible implementation scheme, the waste heat recovery unit includes at least two stages of heat exchangers, multiple heat exchangers are connected in series, and a bypass valve is provided between two heat exchangers.

[0125] In this design, the waste heat recovery unit employs a two-stage heat recovery system. The first stage is a 316L stainless steel plate heat exchanger installed on the diesel engine exhaust manifold; the second stage is an alloy shell-and-tube heat exchanger installed after the turbocharger. The two heat exchangers are arranged in series with an intelligent bypass valve in between. The heat exchanger flow channels are specially designed with an anti-icing structure, with a flow channel width ≥3mm and a surface roughness Ra≤0.8μm, ensuring that ice blockage does not occur in low-temperature environments.

[0126] Based on any of the aforementioned schemes, in one possible implementation scheme, the waste heat recovery unit includes a main heat exchanger module, an auxiliary heat exchanger module, and a supplementary heat exchanger module; the main heat exchanger module, the auxiliary heat exchanger module, and the supplementary heat exchanger module are connected to each other through a controllable valve; the design temperatures of the main heat exchanger module, the auxiliary heat exchanger module, and the supplementary heat exchanger module decrease sequentially.

[0127] In this solution, the waste heat recovery unit adopts an integrated multi-heat source recovery system, comprising three independent heat exchange modules. The main heat exchange module uses a 310S stainless steel plate heat exchanger with a heat exchange area of ​​6.8 m². 2 The design temperature is 650℃; the auxiliary heat exchange module uses a 316L stainless steel tube heat exchanger with a heat exchange area of ​​2.5m². 2Design temperature 300℃; Supplementary heat exchange module: = Uses copper-nickel alloy plate-fin heat exchanger with a heat exchange area of ​​1.8m² 2 The design temperature is 200℃. Each heat exchange module achieves heat coordination through an intelligent valve system, with a valve response time of <100ms.

[0128] Based on any of the aforementioned schemes, in one possible implementation scheme, the thermal storage unit includes a phase change material, and the phase change temperature of the phase change material is 55-65°C.

[0129] In this design, the thermal storage unit is used to achieve peak heat reduction and valley filling. The thermal storage unit and the cooling circulation pipeline are integrated in parallel. This invention preferably uses a composite paraffin-based phase change material with a phase change temperature in the range of 55°C to 65°C. This temperature range has been calculated and experimentally verified: it is much higher than the upper limit of the optimal operating temperature of the battery pack (typically 35°C to 40°C), ensuring that heat can be efficiently transferred to the battery; at the same time, it is significantly lower than the average exhaust temperature (typically >300°C), guaranteeing high charging efficiency from the heat source to the thermal storage unit.

[0130] In this solution, when the internal combustion engine is running at high power and the waste heat output far exceeds the immediate needs of the power battery, the excess heat will be stored in the heat storage unit; when the internal combustion engine is idling, stopped, or the waste heat is insufficient, it will release the stored heat to continuously heat the power battery system, thereby ensuring the continuity and stability of heat.

[0131] In this scheme, the thermal storage unit can adopt a modular design, supporting the use of multiple modules in parallel or series; the thermal storage unit can be equipped with phase change process monitoring sensors and a life prediction system.

[0132] In this scheme, the phase change material can be selected from paraffin-based phase change materials, composite salt phase change materials, hydrated salt phase change materials, or metal alloy phase change materials; the phase change temperature of the phase change material can be selected in the range of 35℃~250℃ according to the specific application scenario.

[0133] In one possible implementation, the thermal storage unit comprises a shaped composite phase change material with a phase change temperature of 58°C, prepared by a mechanized melt blending method using 70% n-octadecane paraffin, 25% high-density polyethylene, and 5% expanded graphite. The total capacity of the thermal storage unit is 85L, with a 316 stainless steel shell and 124 6063 aluminum alloy finned tubes internally arranged with an outer diameter of 8mm and a wall thickness of 1mm. The fins are spaced 5mm apart and 12mm high, resulting in a total heat transfer area of ​​6.2m². 2 The unit is wrapped with a 30mm thick nano-aerogel insulation layer.

[0134] In one feasible implementation, the thermal storage unit employs a modular phase change material (PCM) thermal storage system, consisting of four independent storage modules, each with a capacity of 100L. The PCM is a composite salt-based PCM with a phase change temperature of 218℃ and a phase change enthalpy of 158J / g. The thermal storage unit uses a 310S stainless steel shell, and its internal structure employs a honeycomb ceramic skeleton to enhance thermal conductivity, achieving a total heat transfer area of ​​28.4m². 2 The unit features a double-layer insulation design: an inner layer of 50mm thick microsilica powder insulation board and an outer layer of 30mm thick aluminum foil composite ceramic fiber blanket.

[0135] In one possible implementation, the thermal storage unit comprises a sodium acetate trihydrate-expanded graphite composite phase change material with a phase change temperature of 45°C (85% sodium acetate trihydrate, 12% expanded graphite, and 3% nucleating agent). The total capacity of the thermal storage unit is 120L, using a 316L stainless steel shell (2.5mm thick), and internally arranged with 216 6061 aluminum alloy finned tubes (6mm fin spacing, 15mm height) with an outer diameter of 10mm and a wall thickness of 1mm, providing a total heat transfer area of ​​10.8m². 2 The unit features a double-layer insulation design: the inner layer is a 50mm thick nano-silica aerogel felt, and the outer layer is a 30mm thick polyimide composite insulation material.

[0136] In one feasible implementation, the thermal storage unit employs a dual-temperature zone design. The low-temperature zone uses a stearic acid-lauric acid eutectic mixture with a phase change temperature of 38°C; the high-temperature zone uses an erythritol-graphene oxide composite material with a phase change temperature of 78°C. The two thermal storage units are connected via intelligent temperature-controlled valves, and are housed in 316 stainless steel shells, externally wrapped with an 80mm thick composite insulation layer.

[0137] In one feasible implementation, the thermal storage unit adopts a modular design, with each module having a capacity of 50L, and a standard configuration includes four modules. The module housing is made of 310S stainless steel, and the interior uses a 3D-printed honeycomb ceramic skeleton, which improves the thermal conductivity by 45% compared to traditional designs. Each module is independently equipped with a temperature sensor, flow meter, and insulated valve.

[0138] For example, based on Embodiment 1, the solutions in this embodiment can be arbitrarily combined with the solutions in Embodiment 1.

[0139] For example, as one possible implementation, considering the frequent start-stop and drastic changes in operating conditions during shunting operations, the power battery thermal protection system of a hybrid locomotive can be configured as follows:

[0140] The waste heat recovery unit employs a compact plate heat exchanger made of 316L stainless steel, rigidly connected directly to the diesel engine exhaust manifold outlet via a standard flange. The core dimensions of the heat exchanger are 320mm × 240mm × 85mm, comprising 218 0.4mm thick corrugated stainless steel plates with a herringbone pattern, achieving a total heat exchange area of ​​4.8m². 2 The flow channel design was optimized through computational fluid dynamics simulation, resulting in a pressure drop of only 8.5 kPa under rated operating conditions. The device is designed to operate at a temperature of 650℃ and a pressure of 0.8 MPa.

[0141] The nanofluid's base solution consisted of a 60% (v / v) aqueous solution of ethylene glycol, with 4.0% (w / w) of α-phase alumina nanoparticles surface-modified using KH550 silane coupling agent. The preparation process employed a two-step method: first, mechanical stirring at 2000 rpm for 120 minutes in a high-speed disperser, followed by ultrasonic treatment at 40 kHz frequency and 800 W power for 240 minutes in an ultrasonic processor. Finally, 0.5% (w / w) of polyvinylpyrrolidone was added as a dispersant stabilizer.

[0142] The thermal storage unit incorporates a shaped composite phase change material with a phase change temperature of 58℃, prepared from 70% n-octadecane paraffin, 25% high-density polyethylene, and 5% expanded graphite through a mechanized melt blending method. The total capacity of the thermal storage unit is 85L, featuring a 316 stainless steel shell and internally arranged 124 6063 aluminum alloy finned tubes with an outer diameter of 8mm and a wall thickness of 1mm. The fins are spaced 5mm apart and 12mm high, providing a total heat transfer area of ​​6.2m². 2 The unit is wrapped with a 30mm thick nano-aerogel insulation layer.

[0143] The main controller of the control unit employs a 32-bit multi-core microprocessor, running a predictive control algorithm based on a state-space model. The control system uses a 200ms sampling period to read real-time data from the diesel engine ECU, including engine speed (accuracy ±1 rpm), torque (accuracy ±2%), and fuel flow (accuracy ±1.5%), via the J1939 protocol. It also reads parameters from the BMS, such as battery temperature (accuracy ±0.2℃), SOC (accuracy ±1%), and current (accuracy ±0.5%), via the CAN2.0B protocol. The predictive control algorithm uses constrained multivariable predictive control, with a prediction time domain of 60 steps (12 seconds) and a control time domain of 15 steps (3 seconds). The output uses a 4-20mA analog signal to control the variable frequency pump speed (accuracy ±0.5%) in the cooling circulation pipeline; and a PWM signal to control the valves corresponding to the preheating recovery unit, heat storage unit, and cooling circulation pipeline.

[0144] In this study, winter tests conducted at railway hubs in frigid regions with ambient temperatures ranging from -25°C to -30°C showed that shunting locomotives equipped with this system achieved an average battery pack warming from -25°C to above 0°C after a cold start in an average of 8 minutes and 45 seconds. During long-cycle testing, the battery pack did not require auxiliary electric heating, and the system maintained the battery temperature between 20°C and 35°C. Data recordings showed that the battery range loss due to thermal management was only 2.7% (compared to 18.3% in the control group). Temperature sensor records inside the battery pack showed that the maximum temperature difference was consistently maintained within ±1.8°C, and battery temperature uniformity was improved by 72%.

[0145] For example, as one possible implementation, considering the long-distance, high-load operation characteristics of mainline locomotives, the power battery thermal protection system of a hybrid locomotive can be configured as follows:

[0146] The waste heat recovery unit uses a high-temperature resistant, needle-finned, high-efficiency, compact heat exchanger, measuring 480mm × 360mm × 180mm. It comprises 286 heat exchange tubes with an outer diameter of 12mm and a wall thickness of 1.2mm. Each tube's outer wall is laser-welded with 316L stainless steel needles, resulting in a total heat exchange area of ​​15.6m². 2 Under rated operating conditions, the exhaust side pressure drop is controlled within 12 kPa, which is 40% lower than that of traditional designs.

[0147] The nanofluid selected uses graphene nanosheets as the reinforcing phase. The specifications of the graphene nanosheets are: 5-8 layers, 10-15 μm diameter, and 120-150 m² specific surface area. 2 / g. 2.5% (w / w) of graphene nanosheets were added to a 65% (v / w) aqueous solution of ethylene glycol. The preparation process involved ball milling pretreatment followed by ultrasonic treatment. Finally, 0.8% sodium dodecylbenzenesulfonate was added as a dispersant.

[0148] The thermal storage unit employs a modular phase change material (PCM) thermal storage system, consisting of four independent storage modules, each with a capacity of 100L. The PCM utilizes a self-developed composite salt PCM with a phase change temperature of 218℃ and a phase change enthalpy of 158J / g. The thermal storage unit features a 310S stainless steel shell and an internal honeycomb ceramic skeleton structure to enhance thermal conductivity, achieving a total heat transfer area of ​​28.4m². 2 The unit features a double-layer insulation design: an inner layer of 50mm thick microsilica powder insulation board and an outer layer of 30mm thick aluminum foil composite ceramic fiber blanket.

[0149] The control unit employs a hybrid intelligent algorithm combining a Long Short-Term Memory (LSTM) network with a predictive control algorithm (based on a state-space model). The LTM network structure consists of an input layer (32 neurons), two hidden layers (64 neurons each), and an output layer (16 neurons), using ReLU as the activation function. Training data is derived from long-term historical locomotive operating data, including characteristic parameters such as ambient temperature, diesel engine operating conditions, and battery status. The MPC controller uses a recursive least squares online identification system model with a forgetting factor, with a prediction time domain of 180 seconds and a control time domain of 45 seconds. The control system cycle is 100ms, and the output accuracy is ±0.2%.

[0150] In this scheme, continuous tests conducted on mainline railways demonstrated the system's excellent performance under mainline locomotive operating conditions. At an ambient temperature of -20℃, the battery pack warmed up in 9 minutes and 12 seconds. The hybrid control algorithm reduced system energy consumption by 31.7% compared to traditional PID control, achieving a temperature control accuracy of ±1.2℃. The system operated without any failures during the testing period.

[0151] For example, as one possible implementation, for scenarios with low air pressure and low oxygen content in plateau areas above 3000 meters altitude, the thermal protection system for the power battery of a hybrid locomotive can be set as follows:

[0152] The waste heat recovery unit employs a shell-and-tube heat exchanger made of titanium alloy, installed in the diesel engine exhaust manifold via a flexible corrugated pipe connection. The heat exchanger measures 450mm × 320mm × 200mm and contains 365 titanium alloy heat exchange tubes with an outer diameter of 10mm and a wall thickness of 1.5mm, arranged in an equilateral triangle, achieving a total heat exchange area of ​​11.8m². 2 The heat exchange tubes are machined with 0.5mm high spiral microfins on their outer wall and coated with HK-60 high-temperature anti-oxidation coating. The design operating pressure is 0.6MPa, and the temperature resistance is 700℃.

[0153] The nanofluid's base solution is a 65% (v / v) aqueous solution of a special high-altitude ethylene glycol (freezing point -55°C), with 3.5% (w / w) hexagonal boron nitride nanosheets (average particle size 200 nm, thickness 5 nm). The preparation process includes: pretreatment for 60 minutes in a three-roll mill with a roller gap of 0.1 mm and rotation speeds of 200 / 600 / 800 rpm, followed by ultrasonic treatment at 45 kHz frequency and 1000 W power for 180 minutes. Finally, 0.8% (w / w) of polyvinylpyrrolidone is added as a dispersant and stabilizer.

[0154] The thermal storage unit utilizes a sodium acetate trihydrate-expanded graphite composite phase change material with a phase change temperature of 45℃ (85% sodium acetate trihydrate, 12% expanded graphite, and 3% nucleating agent). The total capacity of the thermal storage unit is 120L, featuring a 316L stainless steel shell (2.5mm thick). Internally, it houses 216 6061 aluminum alloy finned tubes (6mm fin spacing, 15mm height) with an outer diameter of 10mm and a wall thickness of 1mm, providing a total heat transfer area of ​​10.8m². 2 The unit features a double-layer insulation design: the inner layer is a 50mm thick nano-silica aerogel felt, and the outer layer is a 30mm thick polyimide composite insulation material.

[0155] The control unit generates control commands based on the predicted preheating output, the predicted power battery system consumption, and the environmental compensation amount.

[0156] In this study, tests conducted in high-altitude areas demonstrated the system's excellent performance under such conditions. The average heating time of the battery pack at -35℃ was 9 minutes and 23 seconds, and the average system heat recovery efficiency reached 64.7%. Under low-pressure conditions, the battery pack temperature control accuracy reached ±1.5℃, and the system energy consumption was reduced by 18.3% compared to systems designed for use in plains areas.

[0157] For example, as one possible implementation, the thermal protection system for the hybrid locomotive's power battery in cold environments can be configured as follows:

[0158] The waste heat recovery unit employs a two-stage heat recovery system. The first stage is a 316L stainless steel plate heat exchanger installed on the diesel engine exhaust manifold; the second stage is an alloy shell-and-tube heat exchanger installed after the turbocharger. The two heat exchangers are arranged in series with an intelligent bypass valve in between. The heat exchanger flow channels are specially designed with an anti-icing structure, with a flow channel width ≥3mm and a surface roughness Ra≤0.8μm, ensuring that ice blockage does not occur in low-temperature environments.

[0159] The base fluid of the nanofluid is a special low-temperature ethylene glycol mixture, composed of 65% ethylene glycol, 30% propylene glycol, and 5% novel antifreeze additives. 4.2% by mass of graphene-coated copper nanocomposite particles are added.

[0160] The thermal storage unit adopts a dual-temperature zone design. The low-temperature zone uses a stearic acid-lauric acid eutectic mixture with a phase change temperature of 38℃; the high-temperature zone uses an erythritol-graphene oxide composite material with a phase change temperature of 78℃. The two thermal storage units are connected by an intelligent temperature-controlled valve, and are equipped with a 316 stainless steel shell with an 80mm thick composite insulation layer on the outside.

[0161] The control unit adopts a distributed control system architecture. The main controller is equipped with four slave controllers. The control algorithm uses an improved Generalized Predictive Control (GPC), with a prediction time domain of 200 seconds and a control time domain of 50 seconds.

[0162] In this design, the system demonstrated superior performance in extreme low-temperature environments. After a cold start at low temperatures, the battery pack's average warm-up time was 11 minutes and 45 seconds, and the system's heat recovery efficiency remained above 58% at -40°C. The dual-temperature zone PCM design improved the system's thermal efficiency by 23.6%.

[0163] For example, as one possible implementation, for a hybrid locomotive platform with multiple waste heat sources, the hybrid locomotive power battery thermal protection system can be configured as follows:

[0164] The waste heat recovery unit adopts an integrated multi-heat source recovery system, comprising three independent heat exchange modules. The main heat exchange module uses a 310S stainless steel plate heat exchanger with a heat exchange area of ​​6.8 m². 2 The design temperature is 650℃; the auxiliary heat exchange module uses a 316L stainless steel tube heat exchanger with a heat exchange area of ​​2.5m². 2 The design temperature is 300℃; the supplementary heat exchange module adopts a copper-nickel alloy plate-fin heat exchanger with a heat exchange area of ​​1.8m². 2 The design temperature is 200℃. Each module achieves thermal coordination through an intelligent valve system, with a valve response time of <100ms.

[0165] The base fluid of the nanofluid is a 60% ethylene glycol aqueous solution, with 4.5% silica added to coat iron oxide nanoparticles.

[0166] The thermal storage unit adopts a modular design, with each module having a capacity of 50L, and a standard configuration includes four modules. The module shell is made of 310S stainless steel, and the interior uses a 3D-printed honeycomb ceramic skeleton, which improves the thermal conductivity by 45% compared to traditional designs. Each module is independently equipped with a temperature sensor, flow meter, and insulated valve.

[0167] The control unit configuration is based on the NSGA-II multi-objective genetic algorithm, outputting the optimal control strategy every 200ms. The calculation uses the Pareto optimal solution set, and the output is the optimized combination of valve opening and variable frequency pump speed.

[0168] In this solution, the synergy of multiple heat sources improves overall energy efficiency by 27.3%, and reduces battery thermal protection energy consumption to 1.2% of the vehicle's total energy consumption.

[0169] Figure 3 This is a flowchart illustrating the power battery system of the hybrid locomotive in the embodiment. (Refer to...) Figure 3In this embodiment, the working process of the hybrid locomotive power battery system includes:

[0170] The internal combustion engine 1 generates waste heat, and the exhaust heat energy is captured by the waste heat recovery unit 200. The coolant (in the cooling circulation pipe 2) absorbs the waste heat and is then directly transferred to the power battery thermal protection system 3 via the liquid circulation system (the power battery thermal protection system 3 is equipped with a temperature control unit 4, which can independently adjust the coolant flow rate according to the temperature requirements of the power battery). The control unit 100 dynamically adjusts the waste heat recovery and transfer process (including adjusting the coolant flow rate, the output heat of the waste heat recovery unit 200, and the output or stored heat of the heat storage unit 300) according to the operating status of the internal combustion engine and the power battery system. The heat storage unit 300 stores excess heat energy during the waste heat recovery process. When the internal combustion engine stops or the waste heat is insufficient, the control unit 100 controls the heat storage unit 300 to release the heat energy.

[0171] In this embodiment, in any of the aforementioned solutions, by efficiently recovering and utilizing waste heat energy from the internal combustion engine exhaust system, the traditional mode of relying on battery power for heating is completely changed, fundamentally solving the problem of high energy consumption in thermal management. This system achieves cascaded utilization and efficient conversion of energy, significantly reducing overall vehicle energy consumption and greatly improving the comprehensive energy efficiency and range of hybrid electric vehicles.

[0172] Thanks to the efficient and compact heat exchanger design, the application of high thermal conductivity nanofluids, and the precise control of intelligent predictive control algorithms, the system's thermal response speed has been greatly improved. In extreme low-temperature environments, the battery pack can rapidly heat up to its normal operating temperature, fully meeting the stringent requirements of instant start-up and rapid response in rail transit. Simultaneously, the system achieves precise and uniform control of the battery temperature field, effectively eliminating localized overcooling or overheating, and significantly improving the battery system's operational safety and lifespan.

[0173] All system components have been specially designed and verified for the harsh operating environment of locomotives, demonstrating excellent resistance to vibration, high temperatures, and adaptability to complex operating conditions. The intelligent control system possesses multi-source information perception and proactive decision-making capabilities, enabling it to adapt to various complex operating conditions such as internal combustion engine power fluctuations and ambient temperature changes, ensuring stable and reliable operation under all conditions. The system also exhibits good environmental adaptability, capable of being optimized and adjusted for special environments such as high altitudes, extreme cold, and high temperatures.

[0174] By employing multi-source information fusion and intelligent predictive control technologies, the system achieves a fundamental shift from passive response to proactive prediction. Intelligent algorithms, based on multi-dimensional operational data, can predict changes in heat supply and demand in advance and formulate optimal control strategies, achieving precise matching between unstable heat sources and dynamic heat demand. This intelligent thermal management approach significantly improves system energy efficiency while reducing dependence on external conditions.

[0175] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for thermal protection control of a power battery in a hybrid locomotive, characterized in that, include: The control unit is configured to acquire first operating condition data of the internal combustion engine and generate a predicted preheating amount based on the first operating condition data; acquire second operating condition data of the power battery system and generate a predicted power battery system consumption amount based on the second operating condition data; Control commands are generated based on the predicted preheating amount and the predicted power battery system consumption. The control commands are used to determine the output heat of the waste heat recovery unit and the output heat or stored heat of the heat storage unit. The waste heat recovery unit is integrated on the exhaust manifold of the internal combustion engine. The waste heat recovery unit is in contact with the cooling circulation pipeline of the power battery system and the heat storage unit. The heat storage unit is also in contact with the cooling circulation pipeline.

2. The hybrid locomotive power battery thermal protection control method as described in claim 1, characterized in that, Generating the control commands includes: Based on the predicted preheating generation and the predicted power battery system consumption at the current moment, a control sequence within a preset time window is generated. The control sequence includes several control instructions, which are used to determine the opening degree of the first valve of the waste heat recovery unit and the opening degree of the second valve of the heat storage unit at the corresponding moment. The opening degree of the first valve is used to control the output heat of the waste heat recovery unit, and the opening degree of the second valve is used to control the output heat or stored heat of the heat storage unit.

3. The hybrid locomotive power battery thermal protection control method as described in claim 2, characterized in that, The control command is also used to determine the pump speed of the cooling circulation pipeline at a corresponding time, and the pump speed is used for coolant flow control of the cooling circulation pipeline.

4. The thermal protection control method for the power battery of a hybrid locomotive as described in claim 1, characterized in that, Generating the control sequence includes: Acquire environmental data, determine environmental compensation amount based on the environmental data, and generate control commands based on the predicted preheating generation amount, the predicted power battery system consumption amount, and the environmental compensation amount; The environmental data includes at least atmospheric pressure and oxygen content.

5. A hybrid locomotive power battery system, characterized in that, include: Control unit, waste heat recovery unit, and heat storage unit; The waste heat recovery unit is integrated into the exhaust manifold of the internal combustion engine, and the waste heat recovery unit is in contact with the cooling circulation pipeline of the power battery system and the heat storage unit respectively. The heat storage unit is also configured to contact the cooling circulation pipeline; The control unit is configured to acquire first operating condition data of the internal combustion engine and generate a predicted preheating amount based on the first operating condition data; acquire second operating condition data of the power battery system and generate a predicted power battery system consumption amount based on the second operating condition data; Control commands are generated based on the predicted preheating amount and the predicted power battery system consumption. The control commands are used to determine the output heat of the waste heat recovery unit and the output heat or stored heat of the heat storage unit.

6. The hybrid locomotive power battery system as described in claim 5, characterized in that, The coolant in the cooling circulation pipeline is a nanofluid, which includes a base fluid, nanoparticles, and a dispersant.

7. The hybrid locomotive power battery system as described in claim 5, characterized in that, The waste heat recovery unit is also equipped with an automatic cleaning device, which is used to clean the heat exchanger in the waste heat recovery unit.

8. The hybrid locomotive power battery system as described in claim 5, characterized in that, The waste heat recovery unit includes at least two stages of heat exchangers, with multiple heat exchangers connected in series, and a bypass valve is provided between two heat exchangers.

9. The hybrid locomotive power battery system as described in claim 5, characterized in that, The waste heat recovery unit includes a main heat exchanger module, an auxiliary heat exchanger module, and a supplementary heat exchanger module. The main heat exchanger module, auxiliary heat exchanger module, and supplementary heat exchanger module are connected by a controllable valve; the design temperatures of the main heat exchanger module, auxiliary heat exchanger module, and supplementary heat exchanger module decrease sequentially.

10. The hybrid locomotive power battery system as described in claim 5, characterized in that, The thermal storage unit contains a phase change material, and the phase change temperature of the phase change material is 55-65°C.

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