Automobile hydrogen water electric heating circulation method and system

Abstract

The invention provides an automobile hydrogen water electric heating circulation method and system, and the method comprises the steps: obtaining a driving route, a power load and a motor power change trend of an automobile, and generating oxygen use demand references of different driving sections based on multi-source prediction information; an oxygen consumption model is constructed, the target oxygen enrichment proportion is calculated by combining the real-time states of a hydrogen cylinder and an oxygen cylinder and the actual power requirement of a motor, and the oxygen injection flow of the hydrogen fuel cell in different power sections is controlled through sectional type oxygen enrichment scheduling. The system further adjusts the operation power of the water electrolysis hydrogen production device and the canning pressurization proportion of hydrogen and oxygen according to the scheduling result, dynamically adjusts the heat recovery path of the hot water storage tank, and meanwhile, executes safety self-adaptive regulation and control based on oxygen remaining amount prediction, reduces the oxygen enrichment proportion when oxygen is excessive, improves the oxygen enrichment proportion when oxygen is insufficient, and achieves the purpose of energy conservation and emission reduction. And the residual amount of the oxygen cylinder and the vehicle driving demand are synchronously consumed.

Description

Technical Field

[0001] This invention relates to the field of vehicle hydrogen energy management and multi-energy flow coordinated control technology, and in particular to a method and system for automotive hydrogen-water-electric-thermal cycle. Background Technology

[0002] With the development of vehicles towards hydrogen fuel cell power systems, on-board hydrogen energy utilization efficiency, hydrogen production and refueling capabilities, and thermal management have become key factors affecting vehicle performance and safety. Current on-board hydrogen energy systems generally include hydrogen fuel cells, water electrolysis hydrogen production devices, and a certain capacity hot water storage unit. However, existing systems mostly operate independently, lacking comprehensive judgment of the vehicle's real-time operating conditions and failing to achieve coordinated control between hydrogen energy, electrical energy, and thermal energy.

[0003] In real-world driving scenarios, a vehicle's power demands fluctuate constantly with changes in road gradient, steering curvature, traffic conditions, and load, significantly altering the oxygen consumption and power output of hydrogen fuel cells. Current technologies use air as the oxygen source for fuel cells or employ a fixed oxygen flow rate to control oxygen enrichment, making it difficult to precisely match oxygen supply to different operating conditions. This leads to decreased fuel cell efficiency, low oxygen utilization, and the risk of insufficient oxygen supply under high-load conditions. Furthermore, the operation of water electrolysis hydrogen production devices is typically controlled at a fixed power level, which not only fails to dynamically replenish hydrogen based on the vehicle's real-time hydrogen consumption but also places an additional burden on the vehicle's power supply, resulting in inefficient energy distribution.

[0004] Therefore, we propose a method and system for hydrogen-water electrothermal cycle in automobiles. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by providing a method and system for hydrogen-water electrothermal cycle in automobiles, thereby resolving the technical problems mentioned in the background section.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for a hydrogen-water electrothermal cycle in automobiles includes the following steps:

[0008] S1. Obtain vehicle operation prediction information and generate oxygen demand benchmark: Obtain navigation route, vehicle load, vehicle acceleration characteristics and motor power change trend through the vehicle controller, and calculate the oxygen demand benchmark of hydrogen fuel cell in different driving sections based on the operation prediction information, so as to serve as the input parameter for subsequent oxygen-enriched mode scheduling.

[0009] S2. Calculate the target oxygen enrichment ratio based on the oxygen consumption model: Based on the oxygen usage demand benchmark, combined with the hydrogen cylinder pressure, oxygen cylinder pressure and the current power demand of the motor, construct an oxygen consumption model, and obtain the target oxygen enrichment ratio for the corresponding driving section based on the oxygen consumption model. The target oxygen enrichment ratio is used to indicate the oxygen injection flow rate required by the hydrogen fuel cell in different sections.

[0010] S3. Perform segmented oxygen-enriched scheduling control of hydrogen fuel cells: Based on the target oxygen enrichment ratio, control the hydrogen fuel cells to enter the segmented oxygen enrichment mode, so that the oxygen injection flow rate of the hydrogen fuel cells is increased in the high power demand section and decreased in the low power demand section, so as to achieve coordinated control of oxygen on demand distribution and power output on efficiency.

[0011] S4. Based on the oxygen-enriched scheduling results, perform energy distribution of hydrogen-water-electricity cycle: According to the oxygen-enriched scheduling results, dynamically adjust the operating power of the water electrolysis hydrogen production device, the pressurization ratio of hydrogen and oxygen, and the heat recovery path of the hot water storage tank, so that hydrogen energy, electrical energy and heat energy can be distributed in real time in the vehicle hydrogen-water-electricity cycle system.

[0012] S5. Safety-adaptive control based on oxygen reserve prediction: Based on the energy distribution results and oxygen cylinder remaining capacity prediction information, determine whether the oxygen reserve before the vehicle reaches the target area meets the safety threshold; when the oxygen reserve is higher than the threshold, increase the oxygen enrichment ratio to accelerate oxygen consumption; when the oxygen reserve is lower than the threshold, decrease the oxygen enrichment ratio to ensure that the fuel cell maintains stable efficiency, thereby achieving synchronous consumption of oxygen cylinder remaining capacity and vehicle driving needs.

[0013] S1 specifically involves: acquiring information related to the vehicle's driving route, road gradient, steering curvature, and expected congestion through the vehicle navigation system, serving as the foundational data for predicting the vehicle's future power demand; collecting information on the vehicle's current load, acceleration habits, average torque demand, and historical energy consumption curves to characterize changes in the vehicle's power demand under different operating conditions; extracting acceleration frequency, peak power occurrence period, and stable power ratio indicators based on the vehicle's recent motor power output records to predict the instantaneous power demand for subsequent driving segments; and inputting the collected data into the prediction model to obtain the oxygen usage demand benchmarks for different driving segments, serving as the input basis for subsequently establishing the target oxygen enrichment ratio.

[0014] S2 specifically involves: acquiring hydrogen cylinder pressure, hydrogen temperature, and oxygen cylinder pressure to form real-time status data on the fuel supply side; acquiring instantaneous motor power, motor torque, and battery output current data via the vehicle power bus to calibrate prediction accuracy; constructing an oxygen consumption model reflecting the relationship between oxygen enrichment ratio and power demand based on oxygen usage demand benchmarks, gas state parameters, and motor power demand data; and obtaining the target oxygen enrichment ratio for different driving segments based on the oxygen consumption model, which serves as the execution parameter for subsequent oxygen enrichment scheduling.

[0015] S3 specifically involves: determining whether the current vehicle's driving segment is in a high-power, medium-power, or low-power range based on the target oxygen enrichment ratio; when determined to be in a high-power range, increasing the oxygen injection flow rate based on the target oxygen enrichment ratio to maintain stable energy output of the hydrogen fuel cell under high load conditions; when determined to be in a low-power range, decreasing the oxygen injection flow rate based on the target oxygen enrichment ratio to match oxygen consumption with motor demand and improve oxygen utilization efficiency; merging the execution results to generate the actual oxygen enrichment scheduling result under the current driving state, which serves as the basis for subsequent energy allocation.

[0016] S4 specifically involves: determining the required hydrogen production power of the water electrolysis hydrogen production unit based on the actual oxygen-enriched scheduling results to maintain consistency between hydrogen supply and vehicle demand; calculating the actual production of hydrogen and oxygen based on the hydrogen production power and adjusting the filling ratio of the pressurization unit to ensure that the high-pressure hydrogen cylinder and high-pressure oxygen cylinder maintain reasonable storage levels simultaneously; dynamically adjusting whether heat is prioritized for supplying the air conditioning system or for heating the electrolyte based on the fuel cell's operating mode to optimize heat recovery and hydrogen production efficiency in a coordinated manner; and integrating the execution results into real-time energy allocation results to guide subsequent safety control.

[0017] S5 specifically involves: obtaining oxygen cylinder remaining capacity prediction information based on real-time energy allocation results and vehicle remaining driving range prediction; comparing the oxygen cylinder remaining capacity prediction information with a preset safety threshold to determine whether the current oxygen remaining is too high or too low; increasing the target oxygen enrichment ratio to accelerate oxygen consumption when the oxygen remaining is higher than the threshold; decreasing the target oxygen enrichment ratio to ensure stable fuel cell efficiency when the oxygen remaining is lower than the threshold; and using a control strategy to ensure that the remaining oxygen in the cylinder is consumed synchronously with the vehicle's remaining driving demand, thereby achieving adaptive safety control of the hydrogen-water electrothermal cycle system.

[0018] A car hydrogen-water electrothermal cycle system, comprising:

[0019] The vehicle operation prediction module is used to obtain the vehicle's driving route, load parameters, and motor power change trend, and generate an oxygen demand benchmark based on the operation information to indicate the oxygen demand in different driving sections.

[0020] The oxygen consumption calculation module is used to build an oxygen consumption model based on the baseline of oxygen usage demand, combined with the real-time pressure and temperature of hydrogen and oxygen cylinders and the actual power demand of the motor, and to calculate the target oxygen enrichment ratio for different driving sections based on the model.

[0021] The segmented oxygen enrichment scheduling module is used to control the oxygen injection flow rate of the hydrogen fuel cell to increase the oxygen injection flow rate in the high-power section and decrease the oxygen injection flow rate in the low-power section according to the target oxygen enrichment ratio, and generate the corresponding actual oxygen enrichment scheduling results.

[0022] The hydrogen-water-electricity cycle energy distribution module is used to adjust the operating power of the water electrolysis hydrogen production unit, the pressurization ratio of hydrogen and oxygen, and the heat recovery path of the hot water storage tank according to the actual oxygen enrichment scheduling results, so that hydrogen energy, electrical energy and heat energy are coupled and distributed in real time within the system.

[0023] The safety adaptive control module is used to determine whether the remaining oxygen level meets the safety threshold based on the energy distribution results and the predicted remaining oxygen cylinder capacity. When the remaining oxygen level is too high, the oxygen enrichment ratio is reduced; when the remaining oxygen level is too low, the oxygen enrichment ratio is increased, so as to achieve synchronous consumption of the remaining oxygen cylinder capacity and the vehicle's driving needs.

[0024] The beneficial effects of this invention are as follows:

[0025] This invention generates an oxygen demand baseline by combining route information, power load, and motor power change trends, and constructs an oxygen consumption model to calculate the target oxygen enrichment ratio. This enables precise matching of oxygen supply with the instantaneous power demand of the vehicle. Compared with fixed flow or simple load response methods, it can significantly improve the energy efficiency and power response speed of fuel cells.

[0026] This invention significantly reduces unnecessary oxygen injection by implementing high, medium, or low oxygen enrichment strategies across different power ranges, thereby significantly improving oxygen utilization, reducing oxygen cylinder capacity requirements, and enhancing vehicle safety. Based on actual oxygen enrichment scheduling results, the invention dynamically adjusts the hydrogen production power from water electrolysis, the hydrogen-oxygen tank ratio, and the heat recovery path of the hot water storage tank, enabling the synergistic utilization of waste heat from hydrogen production, the electrolyzer, and the fuel cell. This improves overall vehicle energy efficiency and reduces energy waste.

[0027] This invention dynamically adjusts the oxygen enrichment ratio based on oxygen reserve predictions, ensuring that the remaining oxygen level in the cylinders is consumed in sync with the vehicle's remaining driving demand. This avoids the safety hazard of excessive residual oxygen when the vehicle enters densely populated areas and prevents insufficient oxygen supply during long-distance, high-load operations. By unifying the prediction model, scheduling model, energy distribution module, and safety control module, the onboard hydrogen energy system maintains stable, efficient, and safe operation under various road environments and load conditions, improving the overall vehicle performance and user experience.

[0028] This invention restructures the infrastructure-dependent model of hydrogen refueling and proposes a new paradigm for distributed in-situ hydrogen production based on the existing power grid. Utilizing the characteristics of the main and byproducts of the water electrolysis reaction, this system transforms the "idle window" of parking and charging into a "high-efficiency hydrogen production period," essentially endowing the widely distributed charging pile network with the function of hydrogen refueling stations, effectively overcoming the current industry bottlenecks of high construction costs and low network density of hydrogen refueling stations. This solution not only maximizes the reuse of existing power infrastructure but also achieves deep coupling and closed-loop high-value utilization of material and energy flows by converting the byproduct oxygen into a power enhancer during vehicle operation. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of a hydrogen-water electrothermal cycle method for automobiles according to the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] Example 1: As Figure 1 As shown, this embodiment provides a method for hydrogen-water electrothermal cycle in automobiles, including the following steps:

[0032] S1. Obtain vehicle operation prediction information and generate oxygen demand benchmark: Obtain navigation route, vehicle load, vehicle acceleration characteristics and motor power change trend through the vehicle controller, and calculate the oxygen demand benchmark of hydrogen fuel cell in different driving sections based on the operation prediction information, so as to serve as the input parameter for subsequent oxygen-enriched mode scheduling.

[0033] S2. Calculate the target oxygen enrichment ratio based on the oxygen consumption model: Based on the oxygen usage demand benchmark, combined with the hydrogen cylinder pressure, oxygen cylinder pressure and the current power demand of the motor, construct an oxygen consumption model, and obtain the target oxygen enrichment ratio for the corresponding driving section based on the oxygen consumption model. The target oxygen enrichment ratio is used to indicate the oxygen injection flow rate required by the hydrogen fuel cell in different sections.

[0034] S3. Perform segmented oxygen-enriched scheduling control of hydrogen fuel cells: Based on the target oxygen enrichment ratio, control the hydrogen fuel cells to enter the segmented oxygen enrichment mode, so that the oxygen injection flow rate of the hydrogen fuel cells is increased in the high power demand section and decreased in the low power demand section, so as to achieve coordinated control of oxygen on demand distribution and power output on efficiency.

[0035] S4. Based on the oxygen-enriched scheduling results, perform energy distribution of hydrogen-water-electricity cycle: According to the oxygen-enriched scheduling results, dynamically adjust the operating power of the water electrolysis hydrogen production device, the pressurization ratio of hydrogen and oxygen, and the heat recovery path of the hot water storage tank, so that hydrogen energy, electrical energy and heat energy can be distributed in real time in the vehicle hydrogen-water-electricity cycle system.

[0036] S5. Safety-adaptive regulation based on oxygen reserve prediction: Based on the energy distribution results and oxygen cylinder remaining capacity prediction information, determine whether the oxygen reserve before the vehicle reaches the target area meets the safety threshold; when the oxygen reserve is higher than the threshold, reduce the oxygen enrichment ratio to accelerate oxygen consumption; when the oxygen reserve is lower than the threshold, increase the oxygen enrichment ratio to ensure that the fuel cell maintains stable efficiency, thereby achieving synchronous consumption of oxygen cylinder remaining capacity and vehicle driving needs.

[0037] S1 specifically includes the following sub-steps:

[0038] S110. Obtain route-related information: The vehicle's driving route and its associated road parameters are obtained in real time through the vehicle navigation system, including road slope θ(x), road curvature κ(x), road resistance coefficient μ(x), and traffic congestion level C(x), where x represents the vehicle's location.

[0039] The navigation system generates a route parameter set:

[0040] R = {θ(x),κ(x),μ(x),C(x)}

[0041] The route parameter set is used to characterize the potential changes in vehicle power demand at different locations, serving as the first type of input for subsequent oxygen consumption prediction.

[0042] S120. Obtain vehicle power load information: Collect load parameters reflecting the vehicle's power status via the vehicle power bus, including the vehicle's total mass m, driving behavior acceleration distribution a(t), and average driving torque τ. avg And the historical energy consumption curve E(t).

[0043] The load parameter set is represented as

[0044] L={m,a(t),τ avg ,E(t)}

[0045] Wherein, a(t) is acquired by an accelerometer and smoothed through a time window T.

[0046]

[0047] E(t) is provided by the vehicle's BMS (Battery Management System) and is used to model the energy consumption patterns of the vehicle under different operating conditions.

[0048] The load parameter set L, together with the route parameter set R, is used to construct the power demand trend.

[0049] S130. Obtain the trend of motor power change: Construct the trend of future power demand based on the historical power data P(t) of the motor. Its calculation method uses a sliding window prediction model:

[0050]

[0051] Where α, β, and γ are model weighting coefficients, satisfying α+β+γ=1; ΔP=P(t)-P(tT) characterizes the rate of power change; Δt is the prediction time domain, such as 2–5 seconds.

[0052] The motor power trend set is defined as follows:

[0053]

[0054] This trend set reflects short-term future energy demand and is the third type of input for oxygen demand forecasting.

[0055] S140. Generate oxygen demand baseline: Combine route parameter set R, load parameter set L, and motor power trend set P. trend Input the oxygen demand forecasting model to calculate the baseline oxygen demand (O2) for future driving segments. base .

[0056] The oxygen demand forecasting model uses a weighted hierarchical summation structure:

[0057] O base =w1·f1(R)+w2·f2(L)+w3·f3(P trend )

[0058] Where f1(R) represents the basic oxygen requirement calculated based on slope, curvature, and congestion; f2(L) represents the load correction calculated based on vehicle load, acceleration window, and average torque; f3(P) represents the load correction calculated based on vehicle load, acceleration window, and average torque. trend This indicates that oxygen demand is compensated based on future power forecasts; w1, w2, and w3 are weighting coefficients that satisfy:

[0059] w1 + w2 + w3 = 1

[0060] The final oxygen usage requirements for different driving sections are expressed as follows:

[0061] O base ={O1,O2,…,O n}

[0062] Among them, O iThe target oxygen consumption or target oxygen enrichment ratio of the vehicle in the i-th driving segment is the only input reference quantity for the subsequent oxygen consumption model (S230) and the calculation of the target oxygen enrichment ratio (S240).

[0063] Furthermore, based on the oxygen demand benchmarks for different driving sections, the total oxygen consumption of the vehicle during the entire navigation journey is calculated cumulatively. This predicted value serves as the control target for the charging / hydrogen production stage, determining the production capacity of the water electrolysis hydrogen production device and the storage capacity of the oxygen cylinder, thereby determining the initial cylinder state collected in step S210 (i.e., the state when the vehicle has completed recharging and is ready to depart).

[0064] S2 specifically includes the following sub-steps:

[0065] S210. Real-time status acquisition of hydrogen and oxygen cylinders: Real-time parameters of hydrogen and oxygen cylinders are collected and recorded through the vehicle-mounted gas management module, including hydrogen cylinder pressure. Hydrogen cylinder temperature Oxygen cylinder pressure Oxygen cylinder temperature And combined with the bottle volume V b Calculate the real-time available hydrogen and oxygen quantities.

[0066] The real-time mass of each type of gas is expressed by the ideal gas law as follows:

[0067]

[0068] Where R is the gas constant.

[0069] The obtained real-time gas state set is represented as follows:

[0070]

[0071] The gas state set G serves as the first type of input to the oxygen consumption model (S230).

[0072] S220, Acquiring actual motor power requirements: Real-time acquisition of motor output power P via vehicle power bus. act (t), motor torque τ(t), battery output current I bat (t), and calibrate the predicted power in S130 based on the instantaneous power change rate.

[0073] The instantaneous power change rate is defined as:

[0074] ΔP act (t)=P act (t)-P act (t-Δt)

[0075] Calculate the predicted calibration deviation:

[0076]

[0077] in, The predicted power is obtained from S130.

[0078] The calibrated motor power requirement is:

[0079]

[0080] Where k is the calibration gain coefficient.

[0081] Forming a set of motor power requirements:

[0082] P req ={P adj (t),ΔP act (t)}

[0083] After combining the above motor power requirements with the energy efficiency target, the oxygen demand for fuel cell enrichment can be obtained, that is, the amount of oxygen consumed to inject pure oxygen into the air to improve the efficiency of electrochemical reaction, which serves as the second type of input to the oxygen consumption model (S230).

[0084] S230. Establish an oxygen consumption model: Combine the gas state set G from step S210 and the motor power demand set P from step S220. req And the oxygen usage requirement benchmark O of S140 base Input them into the oxygen consumption model to generate oxygen demand for different power ranges.

[0085] The oxygen consumption model adopts an "oxygen-enriched correction structure based on energy demand," and the model form is as follows:

[0086] (1) Calculation of basic oxygen requirement:

[0087] Theoretical oxygen requirement for fuel cells:

[0088] O theory =a·P adj (t)

[0089] Where 'a' is the oxygen consumption conversion coefficient determined based on the target energy conversion efficiency. This formula reflects the fuel cell output power P at the target energy conversion efficiency (typically set in the range of 50%-65%). adj (t) The theoretical oxygen supply required.

[0090] The physical mechanism is that the energy conversion efficiency of a fuel cell increases with the increase of oxygen concentration at the cathode input; therefore, the higher the target efficiency value, the higher the required oxygen concentration and the corresponding oxygen consumption. theoryThe larger the oxygen supply, the greater the electrochemical polarization loss.

[0091] (2) Safety correction amount based on the real-time status of the oxygen cylinder:

[0092] Based on the oxygen cylinder pressure change rate

[0093]

[0094] Obtain the safety correction amount:

[0095]

[0096] Where b is the security weight.

[0097] (3) Predicted compensation amount based on driving demand benchmark:

[0098] From S140:

[0099] O base ={O1,O2,…,O n}

[0100] Predicted compensation amount:

[0101] O comp =c·O base

[0102] (4) Final oxygen requirement:

[0103] Combining the three factors, the oxygen demand model output is obtained:

[0104] O need =O theory +O safe +O comp -O air

[0105] Among them O air It indicates the amount of oxygen available from the air.

[0106] Model parameters a, b, and c satisfy:

[0107] a + b + c = 1

[0108] The oxygen demand output set is defined as:

[0109]

[0110] in, This represents the actual oxygen demand for the i-th travel segment.

[0111] S240. Calculate the target oxygen enrichment ratio: Based on the oxygen demand output obtained in step S230... needAvailable oxygen levels in vehicles (From S210), calculate the target oxygen enrichment ratio λ(x) for each driving section.

[0112] The target oxygen enrichment ratio is defined as:

[0113]

[0114] To avoid excessively high oxygen levels in certain sections affecting the total mileage, a normalization factor η is introduced:

[0115] λ final (x)=η·λ(x)

[0116] η is dynamically adjusted by the vehicle's remaining mileage prediction model to match the total oxygen consumption with the remaining hydrogen.

[0117] The final target oxygen enrichment ratio set is as follows:

[0118] Λ={λ final (1),λ final (2),…,λ final (n)}

[0119] This result serves as the sole input parameter for subsequent segmented oxygen-enriched scheduling control of S310–S340, and as an estimate of the amount of oxygen required to be stored during water electrolysis for hydrogen production.

[0120] S3 specifically includes the following sub-steps:

[0121] S310. Select oxygen-enriched sections based on driving segments: Obtain the current driving position x(t) through the vehicle positioning module, determine that the vehicle is currently in the i-th driving segment, and retrieve the target oxygen enrichment ratio λ corresponding to that segment. final (i).

[0122] Based on the oxygen enrichment ratio, oxygen-enriched zones are classified as follows:

[0123] When λ final (i)≥λ high This section has been identified as a high-power oxygen-rich zone.

[0124] When λ low ≤λ final (i)<λ high This section was determined to be a medium-power oxygen-rich zone.

[0125] When λ final (i)<λ low It was determined to be a low-power oxygen-rich section.

[0126] Where, λ high and λ lowThe adaptive range threshold is automatically adjusted by the system based on the vehicle's power demand and oxygen reserve prediction results.

[0127] The segment classification output is as follows:

[0128] Z(i)∈{high-power segment, medium-power segment, low-power segment}

[0129] The segment classification Z(i) serves as the entry condition for the next step of the oxygen-enriched scheduling execution logic.

[0130] S320. Perform oxygen-enriched scheduling in high-power sections: When step S310 determines that Z(i) = high-power section, according to the target oxygen-enriched ratio λ final (i) Increase the oxygen injection flow rate.

[0131] The oxygen injection flow rate is calculated as follows:

[0132]

[0133] Among them, Q base Standard oxygen flow rate for fuel cells; The oxygen injection flow rate for the current section.

[0134] This scheduling method enables hydrogen fuel cells to maintain high-efficiency output in high-load sections while improving power response speed.

[0135] The execution result is recorded as follows:

[0136]

[0137] S330. Perform oxygen-enriched scheduling in low-power sections: When step S310 determines that Z(i) = low-power section, reduce the oxygen injection flow rate to ensure that oxygen consumption matches the low-power demand of the vehicle.

[0138] The oxygen injection flow rate in the low-power section is:

[0139]

[0140] Where δ is the low-power reduction factor, satisfying 0 < δ < 1; λ final (i) comes from S240 and is the unique input to the algorithm.

[0141] The execution result is recorded as follows:

[0142]

[0143] This scheduling method significantly reduces unnecessary oxygen consumption, improves oxygen utilization, and is closely coupled with subsequent safety controls (S510–S540).

[0144] S340. Generate actual oxygen-enriched scheduling results: Integrate the execution results of step S320 (high power) and step S330 (low power) into a unified whole.

[0145] The actual oxygen-enrichment scheduling result of the defined section is as follows:

[0146]

[0147] The results for the medium power range can be obtained through actual linear interpolation:

[0148] R mid (i)=Q base ·λf inal (i)

[0149] And summarize them into the final oxygen-enrichment scheduling result set:

[0150] R actual ={R actual (1),R actual (2),…,R actual (n)}

[0151] This result set will serve as the sole input source for the subsequent S410–S440 “energy distribution control”, enabling a continuous closed loop from predicted oxygen enrichment ratio → actual fuel cell scheduling → energy distribution in the hydrogen-water-electricity cycle.

[0152] S4 specifically includes the following sub-steps:

[0153] S410. Adjust the operating power of the water electrolysis hydrogen production unit: Based on the actual oxygen enrichment scheduling result R obtained in S340. actual (i) Calculate the amount of hydrogen required for each driving segment to determine the operating power of the water electrolysis hydrogen production unit.

[0154] (1) Calculation of hydrogen demand for fuel cells:

[0155] The hydrogen requirement of the fuel cell in section i is:

[0156]

[0157] Where, α fc The hydrogen-oxygen consumption ratio is determined by the stoichiometric characteristics of the fuel cell.

[0158] (2) Current amount of hydrogen available in the hydrogen cylinder It originates from S210.

[0159] (3) Δ Hydrogen deficit

[0160] (4) Calculation of operating power for water electrolysis:

[0161] The theoretical power of hydrogen production per unit of water electrolysis is P. unit The operating power of the water electrolysis device is:

[0162]

[0163] Execution result:

[0164] P ele ={P ele (1),…,P ele (n)}

[0165] This forms the basis for subsequent S420 gas filling and control.

[0166] S420. Adjust the filling and pressurization ratio of hydrogen and oxygen: Based on the electrolysis power of water in step S410, calculate the amount of hydrogen and oxygen generated by the water electrolysis device in the i-th section, and adjust the filling ratio of the pressurization device.

[0167] (1) Amount of gas generated by water electrolysis:

[0168] Electrolysis of water reaction formula:

[0169] 2H₂O→2H₂+O₂

[0170] Molar amount of gas produced:

[0171]

[0172] in, and This is the energy conversion ratio coefficient.

[0173] (2) Hydrogen cylinder filling ratio:

[0174]

[0175] (3) Oxygen cylinder filling ratio:

[0176]

[0177] (4) Power distribution of the booster compressor:

[0178] P comp (i)=P ele (i)·η comp

[0179] Where, η comp This is the power ratio coefficient for the booster compressor.

[0180] Output canning ratio set:

[0181]

[0182] S430, Adjust the heat recovery path of the hot water storage tank: Determine the distribution method of heat between the fuel cell and the electrolyzer based on the actual oxygen enrichment scheduling results and the electrolysis power.

[0183] (1) Calculation of heat release from fuel cells:

[0184] Heat release from fuel cells:

[0185] Q fc (i)=β fc ·R actual (i)

[0186] (2) Select the heat recovery path according to the operating conditions:

[0187] If this section is a high-power oxygen-rich zone (from S310):

[0188] Q rec (i)=Q fc (i)

[0189] Priority is given to delivering hot water to the hot water tank to ensure heating for the air conditioning system.

[0190] If it is a low-power section:

[0191] Q rec (i)=Q fc (i)+γ ele ·P ele (i)

[0192] At the same time, excess heat from the electrolytic cell heating device is recovered.

[0193] (3) Heat is injected into the hot water tank:

[0194] Q tank (i)=η heat ·Q rec (i)

[0195] Where, η heat This refers to the thermal coupling efficiency.

[0196] S440. Generate real-time energy allocation results: Integrate the calculation results from steps S410–S430 to form the real-time energy allocation vector for this segment:

[0197]

[0198] The final results are summarized into a real-time energy allocation set:

[0199] E = {E(1), E(2), ..., E(n)}

[0200] Each E(i) contains three types of parameters: electrolysis energy, hydrogen and oxygen filling, and heat recovery. It is the only input for the subsequent S510–S540 (safety and oxygen synchronous consumption control).

[0201] The operating power of the water electrolysis hydrogen production unit is adjusted using a dual-mode control strategy based on vehicle status.

[0202] When the vehicle is in operation: the system executes the "electrolysis lockout and oxygen enrichment priority" strategy. At this time, although an oxygen enrichment scheduling result is generated according to S3, in order to ensure the power supply for vehicle operation, the operating power of the water electrolysis hydrogen production unit is forcibly adjusted and locked to 0kW (i.e., shut-down state). The key point of this step is to dynamically adjust the heat recovery path of the hot water storage tank according to the heat generated by oxygen enrichment combustion, and recover the waste heat of the fuel cell;

[0203] When the vehicle is charging: The system executes a "quantitative hydrogen production and replenishment" strategy. At this time, the vehicle is connected to an external power source. Based on the total oxygen and hydrogen consumption predicted in step S1, the system starts the water electrolysis hydrogen production device and adjusts it to its rated power. The generated hydrogen and oxygen are pressurized and injected into the gas cylinder until the gas cylinder pressure meets the predicted travel requirements. Then, the system shuts down and enters standby mode.

[0204] S5 specifically includes the following sub-steps:

[0205] S510: Obtain oxygen cylinder remaining capacity prediction information: Based on the real-time energy distribution results obtained in S440 and combined with the oxygen cylinder status (from S210), predict the remaining oxygen amount for the future driving section.

[0206] (1) Current available oxygen cylinder mass:

[0207]

[0208] (2) Predict future consumption:

[0209] Based on the actual oxygen-enriched scheduling flow R of the preceding S340 actual (i):

[0210]

[0211] Where Δt is the time length of the segment.

[0212] (3) Predicted oxygen balance:

[0213]

[0214] (4) Remaining capacity prediction set:

[0215]

[0216] It serves as the sole input for S520 threshold determination.

[0217] S520. Determine the relationship between the remaining oxygen level and the safety threshold: Calculate the remaining predicted oxygen level from step S510. remain With preset safety threshold O safe Compare them.

[0218] Define the security threshold:

[0219]

[0220] Where κ is the safety ratio coefficient (e.g., 5%–15%); This represents the initial amount of available oxygen.

[0221] Perform a judgment on each segment:

[0222] like This indicates an oxygen surplus state;

[0223] like This indicates a low oxygen level.

[0224] Output section security state set:

[0225] S(i)∈{surplus, deficiency}

[0226] As the control input for S530.

[0227] S530. Implement the oxygen surplus control strategy: Based on the safety state S(i) output by S520, dynamically adjust the target oxygen enrichment ratio obtained by S240.

[0228] Adjustments can be made upwards or downwards.

[0229] (1) Regulation of oxygen surplus state: reduce the oxygen-enriched ratio

[0230] If S(i) = surplus, then reduce the oxygen enrichment ratio to actively consume the excess oxygen:

[0231] λ adj (i)=λ final (i)·(1-δ1)

[0232] Where 0 < δ1 < 1.

[0233] (2) Regulation of oxygen deficiency: Increase the oxygen-enriched ratio

[0234] If S(i) is insufficient, increase the oxygen enrichment ratio to ensure stable fuel cell efficiency.

[0235] λ adj (i)=λ final (i)·(1+δ2)

[0236] Where 0 < δ2 < 1.

[0237] (3) Adjustment of oxygen enrichment ratio:

[0238] To avoid abnormal peak values, amplitude limiting is implemented:

[0239] λ adj-final (i)=min(λ max ,max(λ min ,λ adj (i)))

[0240] Where, λ max The maximum oxygen enrichment ratio that the system can withstand; λ min This represents the minimum oxygen enrichment ratio.

[0241] (4) Set of regulation results:

[0242] Λ adj ={λ adj-final (1),…,λ adj-final (n)}

[0243] This is the only input for the S540.

[0244] S540, Safety control of synchronized oxygen consumption: using the adjusted oxygen enrichment ratio Λ adj The oxygen consumption is recalculated to ensure that the remaining oxygen in the cylinder is consumed in sync with the vehicle's remaining driving needs.

[0245] (1) Recalculate the oxygen consumption of the section:

[0246] O cons (i)=R base ·λ adj-final (i)

[0247] Among them, R base This is the standard oxygen flow rate for fuel cells.

[0248] (2) Remaining oxygen levels after section update:

[0249]

[0250] (3) Synchronization consumption determination conditions:

[0251] The system ensures:

[0252]

[0253] This means that the oxygen was used up just before the end of the journey.

[0254] (4) Complete synchronous consumption control:

[0255] Output the final oxygen synchronization consumption result set:

[0256]

[0257] To ensure maximum safety, the oxygen reserve is matched with driving demand. While the vehicle is in operation, since the water electrolysis hydrogen production unit is shut down (no new gas is replenished), safety control relies entirely on controlling the consumption rate of the existing oxygen inventory.

[0258] Example 2: This example provides a car hydrogen-water electrothermal cycle system, including:

[0259] The vehicle operation prediction module is used to obtain the vehicle's driving route, load parameters, and motor power change trend, and generate an oxygen demand benchmark based on the operation information to indicate the oxygen demand in different driving sections.

[0260] The oxygen consumption calculation module is used to build an oxygen consumption model based on the baseline of oxygen usage demand, combined with the real-time pressure and temperature of hydrogen and oxygen cylinders and the actual power demand of the motor, and to calculate the target oxygen enrichment ratio for different driving sections based on the model.

[0261] The segmented oxygen enrichment scheduling module is used to control the oxygen injection flow rate of the hydrogen fuel cell to increase the oxygen injection flow rate in the high-power section and decrease the oxygen injection flow rate in the low-power section according to the target oxygen enrichment ratio, and generate the corresponding actual oxygen enrichment scheduling results.

[0262] The hydrogen-water-electricity cycle energy distribution module is used to adjust the operating power of the water electrolysis hydrogen production unit, the pressurization ratio of hydrogen and oxygen, and the heat recovery path of the hot water storage tank according to the actual oxygen enrichment scheduling results, so that hydrogen energy, electrical energy and heat energy are coupled and distributed in real time within the system.

[0263] The safety adaptive control module is used to determine whether the remaining oxygen level meets the safety threshold based on the energy distribution results and the predicted remaining oxygen cylinder capacity. When the remaining oxygen level is too high, the oxygen enrichment ratio is reduced; when the remaining oxygen level is too low, the oxygen enrichment ratio is increased, so as to achieve synchronous consumption of the remaining oxygen cylinder capacity and the vehicle's driving needs.

[0264] Among them, the on-board operation prediction module, oxygen consumption calculation module, segmented oxygen enrichment scheduling module, hydrogen-water-electricity cycle energy distribution module, and safety adaptive control module work together to form a multi-energy flow closed-loop control system for hydrogen fuel cells, hydrogen production devices, and heat recovery systems. This enables vehicles to achieve on-demand oxygen injection, real-time hydrogen replenishment, and adaptive heat recovery under different operating conditions, thereby improving the efficiency and safety of the hydrogen-water-electricity-thermal cycle system.

[0265] This invention restructures the infrastructure-dependent model of hydrogen refueling and proposes a new paradigm for distributed in-situ hydrogen production based on the existing power grid. Utilizing the characteristics of the main and byproducts of the water electrolysis reaction, this system transforms the "idle window" of parking and charging into a "high-efficiency hydrogen production period," essentially endowing the widely distributed charging pile network with the function of hydrogen refueling stations, effectively overcoming the current industry bottlenecks of high construction costs and low network density of hydrogen refueling stations. This solution not only maximizes the reuse of existing power infrastructure but also achieves deep coupling and closed-loop high-value utilization of material and energy flows by converting the byproduct oxygen into a power enhancer during vehicle operation.

[0266] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0267] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0268] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0269] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0270] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0271] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0272] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0273] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0274] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0275] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for hydrogen-water electrothermal cycle in automobiles, characterized in that, Includes the following steps: S1. Obtain navigation route, vehicle load, vehicle acceleration characteristics and motor power change trend through the vehicle controller, and calculate the oxygen demand benchmark of hydrogen fuel cell in different driving sections based on the operation prediction information, so as to serve as the input parameter for subsequent oxygen-enriched mode scheduling. S2. Based on the oxygen usage demand baseline, combined with the hydrogen cylinder pressure, oxygen cylinder pressure and the current power demand of the motor, construct an oxygen consumption model, and obtain the target oxygen enrichment ratio for the corresponding driving section based on the oxygen consumption model. The target oxygen enrichment ratio is used to indicate the oxygen injection flow rate required by the hydrogen fuel cell in different sections. S3. Based on the target oxygen enrichment ratio, control the hydrogen fuel cell to enter a segmented oxygen enrichment mode, so that the oxygen injection flow rate of the hydrogen fuel cell is increased in the high power demand section and decreased in the low power demand section, so as to achieve coordinated control of oxygen on demand distribution and power output on efficiency. S4. Based on the oxygen enrichment scheduling results, dynamically adjust the operating power of the water electrolysis hydrogen production unit, the pressurization ratio of hydrogen and oxygen, and the heat recovery path of the hot water storage tank, so as to achieve real-time coordinated distribution of hydrogen energy, electrical energy and heat energy in the vehicle hydrogen-water-electricity circulation system.

2. The method for a hydrogen-water electrothermal cycle in an automobile according to claim 1, characterized in that, It also includes S5, which, based on the energy distribution results and the oxygen cylinder remaining capacity prediction information, determines whether the remaining oxygen level before the vehicle reaches the target area meets the safety threshold; when the remaining oxygen level is higher than the threshold, it increases the oxygen enrichment ratio to accelerate oxygen consumption; when the remaining oxygen level is lower than the threshold, it decreases the oxygen enrichment ratio to ensure that the fuel cell maintains stable efficiency, thereby achieving synchronous consumption of the remaining oxygen level and the vehicle's driving needs.

3. The method for a hydrogen-water electrothermal cycle in an automobile according to claim 1, characterized in that, S1 specifically refers to: The vehicle navigation system obtains information such as the vehicle's driving route, road gradient, steering curvature, and expected congestion, which serves as the basis for predicting the vehicle's future power demand. Collect vehicle current load, vehicle acceleration habits, average torque demand, and historical energy consumption curve load information to characterize the changes in vehicle power demand under different operating conditions; Based on the vehicle's motor power output records over a recent period, indicators such as acceleration frequency, peak power occurrence period, and stable power ratio are extracted to predict the instantaneous power demand for subsequent driving sections. The collected data is then input into the prediction model to obtain the oxygen usage demand benchmarks for different driving sections, which serve as the input basis for establishing the target oxygen enrichment ratio.

4. The method for a hydrogen-water electrothermal cycle in an automobile according to claim 1, characterized in that, S2 specifically refers to: The system acquires hydrogen cylinder pressure, hydrogen temperature, and oxygen cylinder pressure to generate real-time status data for the fuel supply side; it also acquires instantaneous motor power, motor torque, and battery output current data via the vehicle powertrain bus to calibrate prediction accuracy. Based on oxygen demand baselines, gas state parameters, and motor power demand data, an oxygen consumption model reflecting the relationship between oxygen enrichment ratio and power demand is constructed. According to the oxygen consumption model, the target oxygen enrichment ratio corresponding to different driving sections is obtained, which serves as the execution parameter for subsequent oxygen enrichment scheduling.

5. The method for a hydrogen-water electrothermal cycle in an automobile according to claim 1, characterized in that, S3 specifically refers to: Based on the target oxygen enrichment ratio, determine whether the current driving section of the vehicle is in a high-power, medium-power, or low-power range; when it is determined to be a high-power range, increase the oxygen injection flow rate according to the target oxygen enrichment ratio so that the hydrogen fuel cell can maintain stable energy output under high load conditions. When a low-power section is identified, the oxygen injection flow rate is reduced according to the target oxygen enrichment ratio to match oxygen consumption with motor demand and improve oxygen utilization efficiency. The execution status is merged to generate the actual oxygen enrichment scheduling result under the current driving state, which serves as the basis for subsequent energy allocation.

6. The method for a hydrogen-water electrothermal cycle in an automobile according to claim 1, characterized in that, S4 specifically refers to: Based on the actual oxygen-enriched scheduling results, determine the required hydrogen production power of the water electrolysis hydrogen production unit to keep the hydrogen supply consistent with vehicle demand; based on the hydrogen production power, calculate the actual amount of hydrogen and oxygen produced, and adjust the filling ratio of the pressurization unit to keep the high-pressure hydrogen cylinder and high-pressure oxygen cylinder at a reasonable level. Based on the operating mode of the fuel cell, the system dynamically adjusts whether heat is prioritized for supplying the air conditioning system or for heating the electrolyte, thereby optimizing the synergistic effect between heat recovery and hydrogen production efficiency. The results are then integrated into real-time energy allocation to guide subsequent safety controls.

7. The method for a hydrogen-water electrothermal cycle in an automobile according to claim 1, characterized in that, S5 specifically refers to: Based on the real-time energy distribution results and the prediction of the vehicle's remaining driving range, the remaining capacity of the oxygen cylinder is predicted. Compare the predicted remaining capacity of the oxygen cylinder with the preset safety threshold to determine whether the current remaining oxygen is too high or too low.

8. The method for a hydrogen-water electrothermal cycle in an automobile according to claim 2, characterized in that, S5 also includes: increasing the target oxygen enrichment ratio to accelerate oxygen consumption when the oxygen balance is higher than the threshold; decreasing the target oxygen enrichment ratio to ensure stable fuel cell efficiency when the oxygen balance is lower than the threshold; and based on the control strategy, ensuring that the remaining oxygen cylinder volume is consumed synchronously with the vehicle's remaining driving demand, thereby achieving adaptive safety control of the hydrogen-water electrothermal cycle system.

9. A car hydrogen-water electrothermal cycle system, based on the car hydrogen-water electrothermal cycle method according to any one of claims 1-8, characterized in that, include: The vehicle operation prediction module is used to obtain the vehicle's driving route, load parameters, and motor power change trend, and generate an oxygen demand benchmark based on the operation information to indicate the oxygen demand in different driving sections. The oxygen consumption calculation module is used to build an oxygen consumption model based on the baseline of oxygen usage demand, combined with the real-time pressure and temperature of hydrogen and oxygen cylinders and the actual power demand of the motor, and to calculate the target oxygen enrichment ratio for different driving sections based on the model. The segmented oxygen enrichment scheduling module is used to control the oxygen injection flow rate of the hydrogen fuel cell to increase the oxygen injection flow rate in the high-power section and decrease the oxygen injection flow rate in the low-power section according to the target oxygen enrichment ratio, and generate the corresponding actual oxygen enrichment scheduling results. The hydrogen-water-electricity cycle energy distribution module is used to adjust the operating power of the water electrolysis hydrogen production unit, the pressurization ratio of hydrogen and oxygen, and the heat recovery path of the hot water storage tank according to the actual oxygen enrichment scheduling results, so that hydrogen energy, electrical energy and heat energy are coupled and distributed in real time within the system. The safety adaptive control module is used to determine whether the remaining oxygen level meets the safety threshold based on the energy distribution results and the predicted remaining oxygen cylinder capacity. When the remaining oxygen level is too high, the oxygen enrichment ratio is reduced; when the remaining oxygen level is too low, the oxygen enrichment ratio is increased, so as to achieve synchronous consumption of the remaining oxygen cylinder capacity and the vehicle's driving needs.

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