Two-wheeled vehicle hydrogen-light-lithium hybrid power system and control method

Abstract

The invention discloses a two-wheeled vehicle hydrogen-light-lithium hybrid power system and a control method, and belongs to the technical field of hydrogen energy power. The system comprises a photovoltaic power generation unit, a hydrogen fuel cell unit, a lithium battery assembly, a two-wheeled vehicle motor and a control unit. The control method executes an energy management strategy with photovoltaic as the highest priority: monitoring each power and battery charge state in real time; photovoltaic power generation is preferentially utilized to directly drive the motor; when the photovoltaic power is insufficient, hydrogen fuel cell supplementation is started; and based on the system power difference and the battery SOC, deciding charging and discharging of the lithium battery so as to balance the system power. The vehicle endurance, the system energy efficiency and the environmental adaptability are remarkably improved, the dependence on manual inspection and fuel supply is greatly reduced, and the investment of manpower and material resources is remarkably reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of hydrogen energy power technology, in particular to a two-wheeled vehicle hydrogen-light-lithium hybrid power system and control method. BACKGROUND

[0002] Under the strong driving of global energy transformation and carbon neutralization goals, clean energy technology is accelerating the reconstruction of the transportation system. As a zero-carbon energy carrier, hydrogen energy, with its high efficiency and environmental protection, provides an innovative path for the two-wheeled vehicle field that breaks through the limitations of traditional lithium batteries. In recent years, China's hydrogen energy two-wheeled vehicle industry has shown explosive growth, with its core advantages being high energy supplement efficiency, 1-3 minutes of hydrogen refueling to achieve 100-120 kilometers of cruising range, strong environmental adaptability, stable operation in a wide temperature range of -30℃ to 50℃ without range degradation, and zero-carbon emissions in the whole life cycle. These characteristics directly address the pain points of long charging time for electric vehicles and significant performance degradation in low temperature environments.

[0003] Compared with traditional lithium battery electric vehicles, shared hydrogen energy two-wheeled vehicles have a significant advantage in energy supplement efficiency, but their hydrogen storage bottle replacement mechanism poses new operational challenges. The current mainstream models use solid-state hydrogen storage technology, which ensures safety but is limited by hydrogen storage density, requiring manual replacement every 1.5 days on average. This process involves complex steps such as hydrogen cylinder disassembly, transportation, recharging, and safety testing, resulting in an increase of about 30% in annual maintenance costs per vehicle. Especially in shared mobility scenarios, this high-frequency maintenance requirement conflicts with the high turnover rate of vehicles, putting operators under tremendous pressure in terms of manpower scheduling and material reserves. This high-frequency replacement mode not only reduces the actual availability of vehicles but also becomes one of the key factors restricting the large-scale promotion of shared hydrogen energy two-wheeled vehicles. SUMMARY

[0004] To overcome the shortcomings of the prior art, the present application aims to provide a two-wheeled vehicle hydrogen-light-lithium hybrid power system and control method. This system integrates the advantages of long-range hydrogen energy, instant replenishment of photovoltaic, and fast response of lithium batteries, uses intelligent algorithms to achieve efficient collaboration of multiple energy sources, and aims to significantly improve system energy efficiency, environmental adaptability, and operational reliability, extend vehicle operating time, and reduce dependence on manual inspection and fuel replenishment.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present application is as follows: A two-wheeled vehicle hydrogen-light-lithium hybrid power system, comprising a photovoltaic power generation unit, a hydrogen fuel cell unit, a lithium battery assembly, a two-wheeled vehicle motor, and a control unit, the control unit being in communication connection with the photovoltaic power generation unit, the hydrogen fuel cell unit, the lithium battery assembly, and the two-wheeled vehicle motor respectively.

[0006] Further, the photovoltaic power generation unit comprises a solar panel and a first DC / DC converter, and the hydrogen fuel cell unit comprises a hydrogen fuel cell and a second DC / DC converter; The output end of the solar panel is connected to the input end of the first DC / DC converter, the output end of the hydrogen fuel cell is connected to the input end of the second DC / DC converter, the output end of the first DC / DC converter, the output end of the second DC / DC converter, and the DC port of the lithium battery assembly are collectively connected to a common DC bus, and the motor of the two-wheeled vehicle is connected to the common DC bus through a motor driver. The control unit is in communication connection with the first DC / DC converter, the second DC / DC converter, the battery control system of the lithium battery assembly, and the motor driver of the two-wheeled vehicle motor.

[0007] Further, the first DC / DC converter is built-in with an MPPT control module for maximizing solar energy capture efficiency, and the solar panel is arranged in a modular array form on the top of the vehicle body of the two-wheeled vehicle.

[0008] Further, the MPPT control module maximizes solar energy capture efficiency, specifically including: Real-time acquisition of the output voltage and output current of the solar panel, and calculation of the current output power; Based on the current output power and historical power change trend, a hybrid algorithm combining incremental conductance method and fuzzy logic control is adopted to dynamically adjust the working point of the first DC / DC converter; Wherein, the hybrid algorithm runs at a fixed sampling period of not more than 100 ms, and during the fluctuation of light intensity, by comparing the power change rate on both sides of the current working point, the maximum power point of the solar panel is tracked and locked, ensuring that the photovoltaic energy capture efficiency is not less than 98%.

[0009] A control method of a two-wheeled vehicle hydrogen-light-lithium hybrid power system, comprising the following steps: S1. The control unit monitors the power generation of the photovoltaic power generation unit in real time P pv , the driving power demand of the two-wheeled vehicle motor P load , the available power of the hydrogen fuel cell unit P fc , and the state of charge of the lithium battery assembly SOC ; S2. The control unit performs photovoltaic priority direct drive control: when P pv> 0, the control unit controls the first DC / DC converter to transfer all generated power P pv Prioritize direct drive of the two-wheeler motor through the common DC bus; S3. The control unit performs hydrogen energy supplement control: when P pv < P load > 0, start the hydrogen fuel cell unit and control the second DC / DC converter to output available power P fc P pv P fc P load S4. The control unit performs lithium battery dynamic buffer control: calculates the power difference of the system P diff P diff= P pv P fc P load SOC based on the state of charge If P diff > 0 and SOC SOC chargemax , control the first DC / DC converter and / or the second DC / DC converter to charge the lithium battery assembly; If P diff <0 and SOC SOC dischargemin , control the lithium battery assembly to discharge the two-wheeler motor; wherein SOC chargemax is the upper charging threshold, and SOC dischargemin is the lower discharging threshold.

[0010] Further, S4 further comprises: When the real-time SOC of the lithium battery assembly reaches or exceeds the upper charging threshold, forcibly terminate the charging process of the lithium battery assembly; When the real-time SOC of the lithium battery assembly reaches or is lower than the lower discharging threshold, limit further discharge of the lithium battery assembly.

[0011] ​​​​​​​​​​Further, the charge upper threshold and the discharge lower threshold are dynamically adjusted according to the ambient temperature, and the dynamic adjustment comprises: when the ambient temperature is lower than 0℃, the charge upper threshold is reduced from the first standard value to a first offset, and the discharge lower threshold is increased from the second standard value to a second offset; when the ambient temperature is higher than 45℃, the charge upper threshold is reduced from the first standard value to a third offset, and the discharge lower threshold is increased from the second standard value to a fourth offset.

[0012] Further, in S4, a predictive protection is also included: based on the historical operation data of the lithium battery assembly, a prediction model is used to predict the change trend in the future period SOC ; when it is predicted that SOC the charge upper threshold will be approached in the future period, before SOC the actual charge upper threshold is reached, a charge power limiting mode is started to adjust the actual charge power to K times of the current allowed maximum charge power, where 0 K <1.

[0013] Further, in S4, the control unit controls the charging process of the lithium battery assembly, and an intelligent charging strategy based on fuzzy logic and genetic algorithm is used: a double-input single-output fuzzy logic controller is constructed, wherein: the input variables are: charge state deviation Δ SOC and charge current deviation Δ I , Δ SOC is the difference between the current SOC and the target SOC , and Δ I is the difference between the actual charge current and the current allowed maximum charge current; the output variable is: a weight factor α for dynamically adjusting the charging mode; a fuzzy rule base based on expert experience is preset in the fuzzy logic controller, and the fuzzy rule base dynamically outputs the weight factor SOC according to the input Δ I and Δ α ; when Δ SOC is a large positive value and Δ I is a large positive value, the output control signal makes the lithium battery assembly enter the fast charging mode; when Δ SOC is a small value or a negative value and Δ I is a small value, the output control signal makes the lithium battery assembly enter the trickle charging mode; The intelligent charging strategy further comprises globally optimizing the charging parameters using a genetic algorithm, wherein: a fitness function is defined, which is a weighted sum of charging efficiency η , battery temperature rise Δ T and capacity fade rate Δ C / C or a multi-objective optimization function based on a Pareto frontier; 0 A set of charging parameters is determined by iterative optimization of the genetic algorithm, so that the fitness function is optimal or Pareto optimal, and the charging parameters are applied to the fuzzy logic controller to determine the optimal charging curve actually executed.

[0014] Further, in S3, when the available power P fc controlled ramp-up strategy is executed: the output power of the second DC / DC converter is controlled to P fc within a preset time t from the standby state to the target power at a limited power rate, wherein t≤200ms.

[0015] Compared with the prior art, the present application has the following beneficial effects: 1. By innovatively integrating three complementary energy forms of hydrogen fuel cells (high energy density, fast energy replenishment), photovoltaic power generation units (instant energy supply, clean and renewable), and lithium battery components (high power density, millisecond-level response), a multi-source hybrid power architecture is constructed. This architecture is not simply parallel, but through intelligent dynamic power distribution algorithm, it realizes the three-dimensional efficient cooperation of hydrogen energy, light energy and electric energy in energy layer, time layer and space layer. This system fundamentally breaks through the inherent technical bottleneck of single energy two-wheeled vehicles in terms of endurance mileage, energy replenishment time, environmental adaptability and power response, so that the vehicle has both long endurance of hydrogen fuel cells and excellent instantaneous acceleration and climbing performance of lithium battery electric drive system.

[0016] 2. Through the energy supply mode of "photovoltaic priority direct drive and hydrogen energy precise supplement", the instantaneous solar energy is maximized, and the energy conversion link and storage loss are reduced. The local supply of photovoltaic energy directly reduces hydrogen fuel consumption, combined with intelligent energy management, the hydrogen storage bottle replacement or refueling interval can be significantly extended, in high-frequency use scenarios such as shared travel, fuel cost, and operation complexity and cost of manual inspection and bottle replacement can be greatly reduced.

[0017] 3. A closed-loop control system is constructed, which takes real-time power balance as the core and battery state of charge as the key safety constraint. The system embeds an advanced protection mechanism based on prediction model and a safety threshold dynamically adjusted based on temperature, which can comfortably cope with the light intensity fluctuation, load mutation and wide temperature range from-30℃ to 50℃. This not only guarantees the continuity and smoothness of power output, avoids the driving frustration caused by power mutation, but also maintains the health status of lithium battery in all directions, effectively prevents overcharge and overdischarge, prolongs the life of core components, and reduces the failure rate and maintenance cost of the whole life cycle. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The structure diagram of the present application (the control unit is not shown).

[0019] Figure 2 The structure diagram of the present application system for two-wheeled vehicles.

[0020] Figure 3 The flow chart of the method of the present application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below with reference to the drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0022] In the description of the present application, it should be noted that the terms "first", "second" and the like are only for the purpose of description, and cannot be understood as indicating or implying relative importance.

[0023] Example 1, as Figure 1As shown, the present application provides a two-wheeled vehicle hydrogen-light-lithium hybrid power system, which comprises a photovoltaic power generation unit, a hydrogen fuel cell unit, a lithium battery assembly, a two-wheeled vehicle motor and a control unit, and the control unit is in communication connection with the photovoltaic power generation unit, the hydrogen fuel cell unit, the lithium battery assembly and the two-wheeled vehicle motor respectively. The photovoltaic power generation unit is used to convert solar energy into electric energy and provide instant and clean supplementary energy for the system. The hydrogen fuel cell unit is used to convert stored chemical energy (hydrogen) into electric energy through electrochemical reaction efficiently and stably, serving as the main long-endurance energy source of the system. The lithium battery assembly is used to store, buffer and quickly allocate electric energy, and the specific functions include: providing or absorbing high power instantaneously to balance load fluctuation, storing surplus energy of the photovoltaic and fuel cell units, and providing peak power assistance when high power is required. The two-wheeled vehicle motor is used to convert electric energy into mechanical energy to provide direct driving force for the two-wheeled vehicle. The control unit is used to coordinate, optimize and safely manage the energy flow of the whole hybrid power system in real time, and the specific functions include: implementing a hierarchical energy scheduling strategy with photovoltaic priority, hydrogen energy supplement and battery buffering as the core; implementing intelligent charging and discharging management and safety protection based on the state of charge of the lithium battery assembly; and integrating advanced algorithms to achieve global energy efficiency optimization and stable and reliable operation of the system. SOC

[0024] The photovoltaic power generation unit comprises a solar panel and a first DC / DC converter. The photovoltaic power generation unit adopts a modular design, as shown, the solar panel is arranged on the roof of the vehicle to form an expandable array structure, and each panel is equipped with an intelligent monitoring sensor to collect voltage, current and temperature parameters in real time. Figure 2

[0025] Preferably, the first DC / DC converter adopts a Boost topology structure and is built-in with an MPPT control module to maximize solar energy capture efficiency. The specific operation of maximizing solar energy capture efficiency is as follows: The output voltage and output current of the solar panel are collected in real time, and the current output power is calculated; Based on the current output power and historical power change trend, a hybrid algorithm combining incremental conductance method and fuzzy logic control is adopted to dynamically adjust the working point of the first DC / DC converter; The hybrid algorithm runs at a fixed sampling period of not more than 100 ms, and during the fluctuation of light intensity, the power change rate on both sides of the current working point is compared to track and lock the maximum power point of the solar panel, ensuring that the photovoltaic energy capture efficiency is not less than 98%.

[0026] ​​The hydrogen fuel cell unit comprises a hydrogen fuel cell and a second DC / DC converter. The hydrogen fuel cell is preferably a proton exchange membrane fuel cell with a rated power of 1.0-2.0 kW and an operating temperature range of -30℃ to 80℃. The lithium battery assembly is preferably a lithium iron phosphate battery with a capacity of 2-5 kWh and supports a charge / discharge rate of 2C or higher.

[0027] As shown in Figure 2 , preferably, the hydrogen fuel cell and the lithium battery are integrally arranged in the interior of the vehicle body and located at the rear of the vehicle body.

[0028] The output end of the solar panel is connected to the input end of the first DC / DC converter, the output end of the hydrogen fuel cell is connected to the input end of the second DC / DC converter, the output end of the first DC / DC converter, the output end of the second DC / DC converter, and the DC port of the lithium battery assembly are collectively connected to a common DC bus; the two-wheeled vehicle motor is connected to the common DC bus through a motor driver. The control unit is in communication connection with the first DC / DC converter, the second DC / DC converter, the battery control system of the lithium battery assembly, and the motor driver of the two-wheeled vehicle motor, respectively.

[0029] In embodiment 2, the application provides a control method for a two-wheeled vehicle hydrogen-light-lithium hybrid power system, comprising the following steps: S1. The control unit monitors the power generation of the photovoltaic power generation unit in real time P pv , the driving power demand of the two-wheeled vehicle motor P load , the available power of the hydrogen fuel cell unit P fc , and the state of charge of the lithium battery assembly (i.e. the percentage of the current remaining capacity to the total capacity of the battery); SOC S2. The control unit performs photovoltaic priority direct drive control: when P pv > 0, the control unit controls the first DC / DC converter to directly drive the two-wheeled vehicle motor through the common DC bus with all the generated power P pv ; S3. The control unit performs hydrogen energy supplement control: when P pv < P load , the hydrogen fuel cell unit is started and the second DC / DC converter is controlled to output the available power P fc , P pv + P fc ≥ P load ;​ S4. The control unit performs lithium battery dynamic buffer control: calculates the power difference of the system P diff , P diff= P pv + P fc - P load , and makes a charging and discharging decision based on the state of charge SOC : If P diff > 0 and SOC < SOC chargemax (the upper charging threshold), it is determined that there is a surplus of photovoltaic power generation and the battery has a safe charging margin, and then the first DC / DC converter and / or the second DC / DC converter is controlled to charge the surplus power to the lithium battery assembly. The power difference P diff is compared with the real-time acceptable charging power of the lithium battery assembly, and the smaller of the two is taken as the actual charging power.

[0030] If P diff < 0 and SOC > SOC dischargemin (the lower discharging threshold), it is determined that there is a power gap in the system and the battery has a safe discharging margin, and then the lithium battery assembly is controlled to discharge, and the two-wheeled vehicle motor is supplemented with driving power through the common DC bus; the discharging power of the lithium battery assembly is P diff | and the smaller of the two.

[0031] S2 sets photovoltaic power generation as the highest priority energy source and directly connects to the two-wheeled vehicle motor through the common DC bus. When P pv ≥ P load , the system preferentially uses all generated power P pv to directly drive the two-wheeled vehicle motor. And in this process, a 10ms high-speed sampling period is used to monitor the generated power P pv and the driving power demand P loadThe system dynamically adapts to changes in sunlight and load. Based on historical meteorological data and a vehicle load characteristic database, a power prediction model is constructed, which can predict power balance trends 30 seconds in advance. This model optimizes the parameter switching timing of the Maximum Power Point Tracking (MPPT) control algorithm to proactively adapt to dynamic changes in sunlight and load. Simultaneously, a closed-loop control circuit is formed through a PID controller to adjust the operating point of the first DC / DC converter in real time, ensuring that the photovoltaic output power dynamically and accurately matches the motor load demand, prioritizing the maximization of real-time photovoltaic energy consumption and immediate use.

[0032] S4 also includes: When the lithium battery assembly in real time SOC Reaching or exceeding the charging limit threshold SOC chargemax At that time, the charging process of the lithium battery module will be forcibly terminated, regardless of whether there is a surplus in power generation; When the lithium battery assembly in real time SOC When the discharge threshold is reached or falls below the lower discharge limit, further discharge of the lithium battery components is restricted to protect battery health and ensure safe system operation.

[0033] The upper charging threshold and lower discharging threshold are dynamically adjusted based on the ambient temperature. A temperature-controlled system is established by real-time monitoring of the temperature difference between the lithium battery cell surface and the ambient temperature. SOC - The correlation function of internal resistance enables dynamic adjustment of the threshold, specifically including: When the ambient temperature is below 0°C, the upper limit threshold for charging is reduced from a first standard value (e.g., 90%) to a first offset (e.g., 85%), and the lower limit threshold for discharging is increased from a second standard value (e.g., 20%) to a second offset (e.g., 25%). When the ambient temperature is above 45°C, the upper limit threshold for charging is reduced from the first standard value (e.g., 90%) to the third offset (e.g., 88%), and the lower limit threshold for discharging is increased from the second standard value (e.g., 20%) to the fourth offset (e.g., 22%).

[0034] This temperature-adaptive threshold dynamic adjustment mechanism establishes an accurate thermoelectric coupling model and corrects it in real time. SOC Security Window SOC dischargemin , SOC chargemax This effectively suppresses the risk of increased side reaction rate and internal resistance in lithium batteries under extreme temperatures, thereby significantly delaying battery capacity decay and extending battery cycle life by more than 30% while ensuring safe operation of the system across the entire temperature range.

[0035] S4 also includes predictive protection: Based on historical operating data of lithium battery modules, a predictive model is used to predict future periods.SOC trend. The prediction model is preferably a long short-term memory (LSTM) model.

[0036] When it is predicted that SOC the upper charging threshold will be approached within a future period, in SOC the charging power limiting mode is started before the actual upper charging threshold is reached, adjusting the actual charging power to K times of the currently allowed maximum charging power, where 0 K <1.

[0037] When it is predicted that SOC the lower discharging threshold will be approached within a future period, in SOC the scheduling priority of discharging of the lithium battery assembly is raised before the actual lower discharging threshold is reached.

[0038] The ultimate goal of predictive protection is to ensure the driving safety of the whole vehicle. When it is predicted that SOC the lower discharging threshold will be approached within a future period, not only will the scheduling priority of discharging of the lithium battery be raised (including temporarily raising the instantaneous limit value of the maximum allowed discharging power in the battery management system of the lithium battery assembly), but also a hierarchical load management strategy will be started at the whole vehicle level: automatically ensuring the power supply of key loads such as the drive motor and the core controller; at the same time, limiting or cutting off the power consumption of non-essential functions such as the vehicle entertainment system and auxiliary heating. This logic ensures that the vehicle can still maintain basic driving ability and safely reach a charging point or stop even in an extremely low power situation, fundamentally avoiding the major safety risks caused by sudden loss of power or brake assist in driving due to depletion of power.

[0039] Raising the scheduling priority of discharging of the lithium battery assembly includes temporarily raising the discharging weight coefficient of the lithium battery assembly in system power distribution and / or temporarily relaxing the allowed discharging current limit value of the lithium battery assembly.

[0040] In S4, the control unit adopts an intelligent charging strategy based on fuzzy logic and genetic algorithm optimization for the charging process of the lithium battery assembly: A double-input single-output fuzzy logic controller is constructed, wherein: The input variables are: SOC the state of charge deviation Δ I and the charging current deviation Δ SOC , Δ SOC is the difference between the current SOC and the target I , and Δ is the difference between the actual charging current and the currently allowed maximum charging current; α The output variable is: the weight factor for dynamically adjusting the charging modeThe fuzzy logic controller has a pre-built fuzzy rule base based on expert experience. The fuzzy rule base is determined based on the input Δ. SOC With Δ I The weighting factor is dynamically output through fuzzy inference. α ; When Δ SOC It is a large positive value and Δ I When the value is large positive, the output control signal causes the lithium battery module to enter fast charging mode; When Δ SOC For small or negative values ​​and Δ I When the value is small, the output control signal causes the lithium battery component to enter trickle charging mode; The intelligent charging strategy also includes using a genetic algorithm to globally optimize charging parameters, wherein: Define a fitness function, where the fitness function is the charging efficiency. η Battery temperature rise Δ T With capacity decay rate Δ C / C 0 A weighted sum or a multi-objective optimization function based on the Pareto front; By iteratively optimizing using a genetic algorithm, a set of charging parameters is determined so that the fitness function reaches its optimal or Pareto optimal state. These charging parameters are then applied to a fuzzy logic controller to determine the optimal charging curve for actual execution.

[0041] In S3, the prediction model can also predict the optimal start-up power of the hydrogen fuel cell 30 seconds in advance by analyzing historical lighting data, load curves (real-time power demand sequence of the two-wheeled vehicle drive motor over time), and ambient temperature. The optimal start-up power exactly meets or slightly exceeds the predicted power gap. Furthermore, the prediction model updates its weight parameters every 5 minutes to adapt to sudden changes in lighting or load fluctuations. When a sudden change in lighting or load is detected... P pv < P load At any time, the hydrogen fuel cell completes the transition from standby to rated power within 200ms. During the transition, slope control is used to limit the rate of power change to avoid impacting the motor drive system.

[0042] In two-wheeled vehicle systems, this control strategy can effectively reduce the current surge when the motor starts, prevent system instability caused by sudden changes in battery output power, and also improve riding comfort, avoiding the jerking sensation caused by sudden power changes.

[0043] The control unit is preferably an embedded system integrated with a high-performance microprocessor (MCU) or a digital signal processor (DSP). The hardware of the control unit can be implemented by using a commercial embedded processor module that meets the above functional requirements. For example, a microcontroller based on ARM Cortex-M4 / M7 architecture (such as STM32F4 / F7 series of STMicroelectronics) or a digital signal processor based on C2000 architecture (such as TMS320F28379D of Texas Instruments) can be used.

[0044] The solar panel, hydrogen fuel cell, lithium battery assembly, DC / DC converter, and electric motor for two-wheeled vehicle used in the present application are all known electrical devices that can be directly purchased and used in the market, and their structures, circuits, and control principles are all known technologies. Therefore, the structures, circuits, and control principles of the above components are not described in detail.

[0045] Finally, it should be noted that: the above embodiments are only the preferred embodiments of the present application for describing the technical solutions of the present application, but not limiting them, and of course, they are not limiting the patent scope of the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application; that is, any modification or polishing without substantial significance in the main design idea and spirit of the present application, and the technical problems solved are still consistent with the present application, which should be included in the protection scope of the present application; in addition, the technical solutions of the present application are directly or indirectly applied to other related technical fields, which are also included in the patent protection scope of the present application.

Claims

1. A hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle, characterized in that, It includes a photovoltaic power generation unit, a hydrogen fuel cell unit, a lithium battery module, a two-wheeled vehicle motor, and a control unit. The control unit is communicatively connected to the photovoltaic power generation unit, the hydrogen fuel cell unit, the lithium battery module, and the two-wheeled vehicle motor.

2. The hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 1, characterized in that, The photovoltaic power generation unit includes a solar panel and a first DC / DC converter, and the hydrogen fuel cell unit includes a hydrogen fuel cell and a second DC / DC converter. The output of the solar panel is connected to the input of the first DC / DC converter, and the output of the hydrogen fuel cell is connected to the input of the second DC / DC converter. The outputs of the first and second DC / DC converters, as well as the DC port of the lithium battery assembly, are all connected to a common DC bus. The two-wheeled vehicle motor is connected to the common DC bus via a motor driver. The input of the first DC / DC converter and the output of the second DC / DC converter are also connected to different inputs of the lithium battery assembly. The control unit is communicatively connected to the first DC / DC converter, the second DC / DC converter, the battery control system of the lithium battery pack, and the motor driver of the two-wheeled vehicle motor.

3. The hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 2, characterized in that, The first DC / DC converter has a built-in MPPT control module to maximize solar energy capture efficiency; the solar panels are arranged in a modular array on the top of the two-wheeled vehicle.

4. The hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 3, characterized in that, The MPPT control module maximizes solar energy capture efficiency, specifically including: The system collects the output voltage and current of the solar panel in real time and calculates the current output power. Based on the current output power and historical power change trends, a hybrid algorithm combining incremental conductance method and fuzzy logic control is adopted to dynamically adjust the operating point of the first DC / DC converter. The hybrid algorithm operates with a fixed sampling period of no more than 100ms, and during periods of light intensity fluctuation, it tracks and locks the maximum power point of the solar panel by comparing the power change rates on both sides of the current operating point, ensuring that the photovoltaic energy capture efficiency is no less than 98%.

5. A control method for a hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to any one of claims 1-4, characterized in that, Includes the following steps: S1. The control unit monitors the power generation of the photovoltaic power generation unit in real time. P pv The drive power requirements of two-wheeled vehicle motors P load Available power of hydrogen fuel cell unit P fc and the state of charge of lithium battery components SOC ; S2. The control unit executes photovoltaic priority direct drive control: when P pv When the power output is greater than 0, the first DC / DC converter will generate all its power. P pv The two-wheeled vehicle motor is preferentially driven directly via the common DC bus; S3. The control unit executes hydrogen replenishment control: when P pv < P load At that time, the hydrogen fuel cell unit is started and the second DC / DC converter is controlled to output usable power. P fc ,make P pv + P fc ≥ P load ; S4. The control unit performs dynamic buffer control of the lithium battery: calculates the power difference of the system. P diff , P diff= P pv + P fc - P load And based on charge state SOC Make charge / discharge decisions: like P diff > 0 and SOC < SOC chargemax Then, the first DC / DC converter and / or the second DC / DC converter are controlled to charge the lithium battery assembly. like P diff <0 and SOC > SOC dischargemin Then, the lithium battery components are controlled to discharge to the motors of the two-wheeled vehicle; in, SOC chargemax The upper limit threshold for charging, SOC dischargemin This is the lower limit threshold for discharge.

6. The control method for a hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 5, characterized in that, S4 also includes: When the lithium battery assembly in real time SOC When the charging upper limit threshold is reached or exceeded, the charging process of the lithium battery component is forcibly terminated. When the lithium battery assembly in real time SOC When the discharge threshold is reached or falls below the lower discharge limit, further discharge of the lithium battery module is restricted.

7. The control method for a hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 5, characterized in that, The upper limit threshold for charging and the lower limit threshold for discharging are dynamically adjusted based on the ambient temperature. This dynamic adjustment includes: When the ambient temperature is below 0℃, the upper limit threshold for charging will be reduced from the first standard value to the first offset, and the lower limit threshold for discharging will be increased from the second standard value to the second offset. When the ambient temperature is above 45℃, the upper limit threshold for charging will be reduced from the first standard value to the third offset, and the lower limit threshold for discharging will be increased from the second standard value to the fourth offset.

8. The control method for a hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 5, characterized in that, S4 also includes predictive protection: Based on historical operating data of lithium battery modules, a predictive model is used to predict future periods. SOC Trends; When predicted SOC When it approaches the upper limit of charging in the future, SOC Before the actual charging limit is reached, the charging power limiting mode is activated, adjusting the actual charging power to the currently allowed maximum charging power. K times, where 0 < K <1.

9. The control method for a hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 5, characterized in that, In S4, the control unit employs an intelligent charging strategy based on the collaborative optimization of fuzzy logic and genetic algorithms for the charging process of the lithium battery components. Construct a fuzzy logic controller with two inputs and one output, wherein: The input variable is: charge state deviation Δ SOC and charging current deviation Δ I Δ SOC For the present SOC With the goal SOC The difference, Δ I This is the difference between the actual charging current and the current maximum allowable charging current. The output variable is: a weighting factor used to dynamically adjust the charging mode. α ; The fuzzy logic controller has a pre-built fuzzy rule base based on expert experience. The fuzzy rule base is determined based on the input Δ. SOC With Δ I The weighting factor is dynamically output through fuzzy inference. α ; When Δ SOC It is a large positive value and Δ I When the value is large positive, the output control signal causes the lithium battery module to enter fast charging mode; When Δ SOC For small or negative values ​​and Δ I When the value is small, the output control signal causes the lithium battery component to enter trickle charging mode; The intelligent charging strategy also includes using a genetic algorithm to globally optimize charging parameters, wherein: Define a fitness function, where the fitness function is the charging efficiency. η Battery temperature rise Δ T With capacity decay rate Δ C / C 0 A weighted sum or a multi-objective optimization function based on the Pareto front; By iteratively optimizing using a genetic algorithm, a set of charging parameters is determined so that the fitness function reaches its optimal or Pareto optimal state. These charging parameters are then applied to a fuzzy logic controller to determine the optimal charging curve for actual execution.

10. The control method for a hydrogen-photovoltaic-lithium hybrid power system for a two-wheeled vehicle according to claim 5, characterized in that, In S3, the available power output of the second DC / DC converter is controlled. P fc At that time, a controlled slope start-up strategy is executed: the output power of the second DC / DC converter is controlled. P fc At the preset time t The power level rises from standby state to the target power at a limited power change rate, where t≤200ms.

Images