A composite wind power generation system for new energy vehicles

Abstract

This invention discloses a composite wind power generation system for new energy vehicles, relating to the fields of new energy and energy conservation technology. It includes a composite wind energy capture module, an environmental sensing module, a central control module, and an energy management module. The composite wind energy capture module adjusts the blade pitch angle through a micro servo drive unit, switching between minimum wind resistance and maximum wind energy capture states under different operating conditions. The environmental sensing module integrates a forward electromagnetic wave detection matrix, a lateral ultrasonic array, and a flow velocity sensing unit to detect the three-dimensional wind field ahead, compensate for lateral airflow deviations, provide feedback on local actual flow velocity, and transmit the collected data to the central control module. This invention resolves the contradiction between resistance and benefit in vehicle-mounted wind power generation through precise mechanical structure design, multi-dimensional environmental perception, and a decision algorithm based on a rigorous mathematical model; it achieves efficient wind energy capture at the physical level and deep integration of energy flow and airflow at the control level.

Description

Technical Field

[0001] This invention relates to the field of new energy and energy-saving technology, and in particular to a composite wind power generation system for new energy vehicles. Background Technology

[0002] With the continuous evolution of new energy vehicle technology, improving the energy utilization efficiency of the whole vehicle has become one of the core directions of industry development. The kinetic energy resources generated by the interaction between the vehicle and the air medium during driving have received increasing attention. Wind energy, as a widely distributed and renewable environmental energy source, has the potential to be recycled and utilized under specific working conditions.

[0003] Among them, vehicle-mounted wind power generation technology aims to supplement electricity by capturing the energy of relative airflow when a vehicle is moving. Its basic principle is to convert aerodynamics into rotational mechanical energy, and then convert it into electrical energy through a generator for use by the vehicle system or stored in the power battery.

[0004] Existing technologies for utilizing wind energy in vehicles still have significant shortcomings: First, due to their non-adjustable structure, traditional stationary wind power generation devices introduce additional aerodynamic drag that far exceeds their power generation benefits under most driving conditions, resulting in increased net energy consumption and violating the basic principle of energy conservation. Second, current energy recovery systems for new energy vehicles heavily rely on regenerative braking mechanisms, and no effective recovery path has been established for the continuous air resistance energy during driving. Third, there is a lack of accurate modeling of the dynamic balance between wind energy capture and vehicle energy consumption, making it impossible to identify the effective power generation window with positive net energy efficiency. Finally, existing solutions generally neglect the synergistic optimization of the power generation device and the vehicle's aerodynamic performance, failing to achieve a paradigm shift from single-function components to multi-function systems. These problems collectively restrict the practical application and industrialization of vehicle-mounted wind power generation technology. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a composite wind power generation system for new energy vehicles. Through precise mechanical structure design, multi-dimensional environmental perception, and decision-making algorithms based on rigorous mathematical models, it resolves the contradiction between resistance and benefits in vehicle-mounted wind power generation. It achieves efficient wind energy capture at the physical level and deep integration of energy flow and airflow at the control level, providing a new technical approach for optimizing the driving range of new energy vehicles.

[0006] In a first aspect, the present invention provides a composite wind power generation system for new energy vehicles, the system comprising a composite wind energy capture module, an environmental sensing module, a central control module and an energy management module; The composite wind energy capture module is rigidly connected to the vehicle body through a mechanical support, and its form can be switched by means of a retractable central shaft. It captures wind energy using aerodynamically optimized carbon fiber blades, and adjusts the blade pitch angle through a micro servo drive unit to switch between minimum wind resistance or maximum wind energy capture state under different working conditions, thereby driving the generator to achieve energy conversion. The environmental perception module integrates a forward electromagnetic wave detection matrix, a lateral ultrasonic array, and a flow velocity sensing unit to detect the three-dimensional wind field ahead, compensate for lateral airflow deviations, and provide feedback on the actual local flow velocity, respectively, and transmits the collected wind field, atmospheric, and flow velocity data to the central control module. The central control module adopts a dual-core heterogeneous architecture. It performs high-frequency sampling, filtering and servo control through a real-time control core, and performs net benefit evaluation and vector synthesis through a strategy calculation core to determine the net power generation benefit and output instructions to control the operation of other modules, ensuring control accuracy and stability. The energy management module uses a three-stage power conversion circuit to sequentially stabilize the generator output voltage and smooth power pulsation. Then, through a bidirectional DC-DC topology, it completes energy storage with the optimal charging curve based on the power battery's SOC state.

[0007] Preferably, the composite wind energy capture module includes a support mechanism and a blade assembly; The support mechanism includes a multi-level nested central shaft and a drive element that drives the central shaft to rise and fall. The drive element is configured as a shape memory alloy drive unit or a linear electromagnetic actuator with specific phase change characteristics, used to drive the composite wind energy capture module to extend outward from the accommodating cavity inside the vehicle body to a predetermined working height, or to retract to a non-working position flush with the vehicle body outline. The blade assembly includes multiple blades with variable pitch capability, and each blade is equipped with a micro servo drive unit at its root. The micro servo drive unit is controlled by a central control module and is used to dynamically adjust the blade pitch angle under different composite wind speed conditions.

[0008] Preferably, the blade assembly is configured as a vertical axis telescopic structure. In the non-working state, the blade is attached to the outer wall of the central shaft and retracts into the accommodating cavity along with the central shaft. In the working state, after the central shaft is raised, the blade is radially extended to a predetermined rotation radius under the action of centrifugal force or an auxiliary spring.

[0009] Preferably, the environmental sensing module includes: The forward electromagnetic wave detection matrix is ​​deployed at the front of the vehicle body to scan the flow field in front of the vehicle and construct a three-dimensional wind field model to obtain vector information of the ambient wind. The lateral ultrasonic array is deployed on the side of the vehicle body to monitor lateral airflow disturbances and lateral gust parameters. The flow velocity sensing unit is deployed inside the vehicle's air intake or on the windward side of the composite wind energy capture module to provide real-time feedback of flow velocity data at local feature points.

[0010] Preferably, the decision-making logic operating within the central control module is based on the following net benefit assessment model, the relevant calculation formulas of which are as follows: ; In the formula, The net energy gain of the system at the current moment serves as the sole criterion for determining whether the system should perform a form switch. The instantaneous electrical power output by the generator is obtained by integrating the instantaneous values ​​of the generator's output voltage and current. The overall transmission efficiency coefficient of the vehicle powertrain is a dimensionless constant that takes into account the battery charging and discharging efficiency, inverter efficiency, and motor drive losses. This is the increase in drive power caused by the additional air resistance introduced due to the composite wind energy capture module being in operation. To accurately calculate the increase in drive power due to additional air resistance, a fitting algorithm based on real-time aerodynamic parameters is used, and the calculation formula is as follows: ; In the formula, This is a predetermined coefficient, the value of which is determined by wind tunnel testing of the whole vehicle, and is used to correct for ground effect and airflow interference in the actual driving environment of the vehicle; The real-time air density is calculated by the environmental sensing module based on the real-time atmospheric pressure and temperature data. The vehicle's real-time speed is obtained via the onboard CAN bus; The drag coefficient of the vehicle under a specific deployment configuration is obtained from the experimental data mapping table; The effective windward area under a specific deployment configuration; The reference drag coefficient; This represents the windward area under baseline conditions.

[0011] Preferably, the central control module employs a quaternion-based vector synthesis algorithm to efficiently synthesize the vehicle's own translational vector with the random pulsation vector of the ambient wind; the expression for the synthesized effective wind speed is: ; In the formula, This is the equivalent composite wind speed acting on the blades; The predetermined correlation weighting coefficient is used to correct the weakening effect of the vehicle surface boundary layer on wind speed. The ambient wind speed vector is obtained in real time by the environmental sensing module. The angle between the ambient wind direction and the vehicle's direction of travel; The central control module also integrates a Kalman filter for smoothing the wind speed signal collected by the environmental sensing module. The state update equation of the Kalman filter is: ; In the formula, This is the optimal wind speed state estimate after filtering at the current moment; This is the prior prediction value made for the current time based on the state at the previous time step; This is the Kalman gain matrix, used to assign weights between the prediction model and the observed data; The original observation vector is provided by the flow velocity sensing unit; This is the state transition matrix, which describes the mapping relationship between the system state and the observed values.

[0012] Preferably, the central control module is equipped with a self-learning optimization module, which uses historical driving data to iteratively correct the discrimination threshold in the control decision. The corrected adaptive threshold follows the following logic: ; In the formula, The threshold for final judgment by the system; The preset baseline threshold; The influencing factor of the state of charge of the power battery; This is an ambient temperature correction factor used to compensate for mechanical transmission losses at different temperatures.

[0013] Preferably, the energy management module includes a three-stage power conversion circuit; The first stage is an asymmetrical half-bridge buck-boost converter, used to match the generator's output voltage over a wide speed range; The second stage is an intermediate DC bus coupling circuit with power factor correction function, used to smooth out power ripples; The third stage is the battery charging and discharging interface, which is used to inject the processed electrical energy into the power battery.

[0014] Preferably, the system also has the following auxiliary control functions: Resonance suppression logic: The central control module monitors the vibration spectrum of the generator in real time and changes the equivalent stiffness of the transmission system by instantaneously adjusting the electromagnetic load torque of the generator in order to avoid the natural frequency of the structure. Reverse de-icing function: When the ambient temperature is lower than the predetermined threshold, the central control module controls the generator to switch to motor mode, using the Joule heat generated by the windings for heat conduction de-icing, or controls the linear electromagnetic actuator to generate high-frequency micro-vibration to break the ice layer. Safety retraction logic: When the system detects that the ambient wind speed exceeds the safety threshold, a vehicle collision warning occurs, or the sensor signal fails, the composite wind energy capture module is forcibly driven to retract to the position of minimum resistance.

[0015] Secondly, the present invention also provides a composite wind power generation method for new energy vehicles, which applies the composite wind power generation system for new energy vehicles as described above, and the method includes the following steps: S100: The vehicle continuously acquires data on vehicle speed, ambient wind vector, and battery state of charge through the environmental perception module, and performs noise reduction processing using a Kalman filter. S200: The central control module calls the energy balance equation according to the current vehicle operating conditions and calculates the net energy gain value of the composite wind energy capture module between the deployed and retracted states under the current physical conditions. S300. Determine whether the net energy gain value meets the preset triggering conditions. If it does, calculate the optimal extension height and pitch angle based on the synthetic effective wind speed, and drive the composite wind energy capture module to perform a mode switching action. S400: During power generation operation, the maximum power point tracking algorithm is used to adjust the generator load, while continuously monitoring the changes in vehicle energy consumption. If the net income turns negative, the recovery logic is executed. The S500 uses a three-stage power conversion circuit to convert captured energy into DC power that matches the specifications of the power battery and then stores or utilizes it.

[0016] Compared with the prior art, the present invention has significant technical advantages: 1. By using the retractable central shaft and adjustable pitch angle blades of the composite wind energy capture module, combined with the net benefit assessment model and precise algorithm of the central control module, the module shape and blade status are adjusted in real time to ensure that the electricity generated by wind power generation can cover the drive energy consumption caused by additional wind resistance after deducting energy conversion losses, effectively supplementing the power battery power and improving the vehicle's range.

[0017] 2. The blades of the composite wind energy harvesting module adopt aerodynamically optimized geometry, which can be adjusted to the minimum force angle according to the operating conditions to reduce wind resistance. During high-speed cruising, the blade trails can also fill the low-pressure area on the roof to reduce pressure drag. At the same time, the environmental perception module accurately detects the flow field, and the central control module makes real-time adjustments, solving the problem of neglecting aerodynamic coordination in existing technologies and ensuring that the aerodynamic performance of the whole vehicle does not decrease when the system is working.

[0018] 3. A dynamic three-dimensional wind field model is constructed through the multi-sensor units of the environmental perception module. Combined with the dual-core heterogeneous architecture, Kalman filter algorithm, and quaternion vector synthesis algorithm of the central control module, the accurate acquisition and processing of flow field data and wind speed smoothing are achieved, avoiding frequent high-frequency blade pitch changes and reducing mechanical fatigue load. The three-level power conversion circuit of the energy management module can stabilize fluctuating voltage, smooth power pulsation, and execute the optimal charging curve according to the power battery SOC, thereby improving the efficiency of power conversion and storage.

[0019] 4. The system has multiple preset adaptive working modes and can dynamically correct control thresholds through a self-learning optimization module to adapt to different regions, seasons and battery states; it has low-temperature de-icing and mechanical anti-jamming functions, and can be configured with multiple modules to work together to adapt to heavy commercial vehicles; in emergency conditions, it can quickly retract the deployed parts, and forms a double line of defense by combining passive overload protection and active control of the blade material. At the same time, it relies on the bus architecture and redundant power supply to ensure functional safety, solving the problems of poor adaptability and insufficient safety of existing technologies. Attached Figure Description

[0020] Figure 1 This is a block diagram of the overall modular architecture of the system of the present invention.

[0021] Figure 2 This is a schematic diagram of the composite wind energy capture module in its deployed state.

[0022] Figure 3 This is a cross-sectional structural diagram of the composite wind energy capture module in its retracted state.

[0023] Figure 4 This is a schematic diagram of the overall steps of the method of the present invention. Detailed Implementation

[0024] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention. It should be noted that relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0025] Example 1 Please see Figures 1-4This invention provides a composite wind power generation system for new energy vehicles, applied to the roof integration scenario of mid-to-high-end new energy vehicles. The aim is to achieve net energy recovery under typical operating conditions such as high-speed cruising and long downhill slopes, while ensuring that the vehicle's aerodynamic performance is not degraded. The system includes a composite wind energy capture module, an environmental sensing module, a central control module, and an energy management module. Each module achieves high-bandwidth, low-latency data interaction with an Ethernet backbone network via a CAN FD bus, and functional safety is ensured by a dual-power redundant power supply architecture.

[0026] At the mechanical structure level, the composite wind energy capture module is rigidly connected to the vehicle frame through mechanical supports, and its interior houses the support mechanism and generator. The support mechanism adopts a multi-level nested central shaft structure, and the lifting drive of the central shaft is realized by a linear electromagnetic actuator or a lead screw and nut pair, thereby ensuring that the module can perform precise vertical or radial extension and retraction within a predetermined mechanical stroke according to control commands. At the end of the composite wind energy capture module, a set of blade assemblies is installed. These blade assemblies are made of high-strength-toughness carbon fiber composite material, and their geometry has been specifically aerodynamically optimized to maintain a stable lift-to-drag ratio over a wide Reynolds number range. The blade assemblies are supported on the rotor shaft of the generator by precision bearing sets, and each blade has a micro servo drive unit at its root. The micro servo drive unit is used to adjust the blade pitch angle, thereby changing the angle of attack of the blade relative to the composite wind vector to achieve real-time control of aerodynamic torque. When the system detects high vehicle speed conditions and low ambient wind speed, the micro servo drive unit adjusts the blades to the minimum force angle to reduce the basic wind resistance in the deployed state of the module. In the case of regenerative braking, the pitch angle is increased to maximize the wind energy capture area.

[0027] The environmental perception module, serving as the system's data source, integrates a forward electromagnetic wave detection matrix, a lateral ultrasonic array, and a flow velocity sensing unit. The forward electromagnetic wave detection matrix utilizes multi-channel radar beamforming technology to spatially sample the flow field distribution in front of the vehicle, constructing a dynamic three-dimensional wind field model. The lateral ultrasonic array is distributed at the vehicle's side skirts to compensate for airflow angle errors caused by vehicle steering or lateral gusts. The flow velocity sensing unit is deployed within the module's air intake or at key points, providing real-time feedback of the actual local flow velocity. All perception data is transmitted to the central control module via shielded twisted-pair cables or a dedicated vehicle bus.

[0028] The central control module adopts a dual-core heterogeneous processor architecture. The first core is a real-time control core, which is responsible for running high-frequency sampling, Kalman filtering algorithm, and PID control of servo loop. The second core is a strategy operation core, which is responsible for running decision logic based on net benefit evaluation function, self-learning optimization algorithm, and vehicle communication protocol stack. This hardware design ensures that the system has extremely high real-time response speed when processing complex flow field data.

[0029] The core decision-making logic within the central control module is based on a net benefit assessment model. The system must ensure that the electricity generated by wind power, after accounting for energy conversion losses, can still cover the additional drive energy consumption caused by increased wind resistance. This assessment model follows the mathematical expression below: ; In the formula, The net energy gain of the system at the current moment serves as the sole criterion for determining whether the system should perform a form switch. The instantaneous electrical power output by the generator is obtained by integrating the instantaneous values ​​of the generator's output voltage and current. The overall transmission efficiency coefficient of the vehicle powertrain is a dimensionless constant that takes into account battery charging and discharging efficiency, inverter efficiency, and motor drive losses. This is the increase in drive power caused by the additional air resistance introduced due to the operation of the composite wind energy capture module.

[0030] To accurately calculate the increase in drive power caused by the aforementioned additional air resistance This invention employs a fitting algorithm based on real-time aerodynamic parameters, and the calculation formula is as follows: ; In the formula, This is a predetermined coefficient, the value of which is determined by wind tunnel testing of the whole vehicle, and is used to correct for ground effect and airflow interference in the actual driving environment of the vehicle; The real-time air density is calculated by the environmental sensing module based on the real-time atmospheric pressure and temperature data. The vehicle's real-time speed is obtained via the onboard CAN bus; The drag coefficient of the vehicle under a specific deployment configuration is obtained from the experimental data mapping table; This refers to the effective windward area under this configuration; The reference drag coefficient is the module's drag coefficient when it is in the retracted state; This represents the windward area under baseline conditions.

[0031] Furthermore, to obtain accurate synthetic wind speed during dynamic driving, the central control module executes a quaternion-based vector synthesis algorithm. This algorithm can efficiently synthesize the vehicle's own translational vector with the random pulsating vector of the ambient wind; the expression for the synthesized effective wind speed is: ; In the formula, This is the equivalent composite wind speed acting on the blades; The predetermined correlation weighting coefficient is used to correct the weakening effect of the vehicle surface boundary layer on wind speed. The ambient wind speed vector is obtained in real time by the environmental sensing module. The angle between the ambient wind direction and the vehicle's direction of travel.

[0032] Considering the random high-frequency noise generated by road surface undulations and gusts during vehicle operation, the system smooths the input wind speed signal using a Kalman filter. The state update equation of the Kalman filter is defined as follows: ; In the formula, This is the optimal wind speed state estimate after filtering at the current moment; This is the prior prediction value made for the current time based on the state at the previous time step; This is the Kalman gain matrix, used to assign weights between the prediction model and the observed data; The original observation vector is provided by the flow velocity sensing unit; This is the state transition matrix, describing the mapping relationship between the system state and the observed values. Through this filtering mechanism, the micro servo drive unit can obtain stable control input, effectively avoiding frequent pitching operations of the blades under high-frequency disturbances and reducing fatigue loads on the mechanical structure.

[0033] The energy management module, as the hub of power conversion, integrates a three-stage power conversion circuit. The first stage is an asymmetric half-bridge buck-boost converter, which uses soft-switching technology with zero-voltage switching characteristics to stabilize the generator output voltage to the intermediate bus level when the voltage fluctuates significantly due to vehicle speed fluctuations. The second stage is an intermediate DC bus coupling circuit with power factor correction function, which acts as a buffer for system power and can smooth out power pulsations caused by gusts of wind. The third stage is a battery charging and discharging interface, which is connected to the power battery through a bidirectional DC-DC topology and controlled by the central control module, executing the optimal charging curve according to the power battery's SOC (state of charge).

[0034] In practical implementation, this invention pre-sets multiple adaptive operating modes to cope with complex driving environments. In high-speed constant-speed cruise mode, the system prioritizes ensuring smooth airflow. At this time, the deployment height of the composite wind energy harvesting module is finely adjusted according to vehicle speed, allowing the wake generated by the blade assembly to fill the low-pressure area behind the vehicle roof. This reduces vehicle pressure drag through aerodynamic interference while simultaneously generating electricity. In regenerative braking mode, the system enters maximum torque interception mode, with the blade assembly deployed to its maximum frontal area. The resulting aerodynamic drag is not only used for power generation but also serves as an auxiliary braking force to share the load on the mechanical braking system.

[0035] As a key engineering optimization of this invention, the central control module integrates a self-learning optimization module based on weighted least squares. This module can dynamically adjust the decision threshold in the control strategy based on driving data from different regions and seasons; the adjusted adaptive threshold follows the calculation formula: ; In the formula, The threshold for final judgment by the system; The preset baseline threshold; This is an influencing factor on the state of charge of the power battery. When the battery charge is lower than a predetermined safety threshold, this factor is reduced through an exponential mapping function, so that the system can trigger the energy recovery logic even under low wind speeds, prioritizing the protection of power reserves. This is an ambient temperature correction factor used to compensate for mechanical transmission losses at different temperatures.

[0036] The technical effects of the present invention will be quantitatively demonstrated through specific embodiments below.

[0037] In this embodiment, the experimental subject is a standard new energy mid-size sedan with a basic drag coefficient. The effective windward area is 0.23. It measures 2.2 square meters. The composite wind energy capture module is deployed on the center line of the rear of the vehicle roof.

[0038] The vehicle was set to travel at a constant speed of 110 km / h (approximately 30.56 m / s) on a highway. The environmental perception module detected an ambient wind speed of 8 m / s, with the wind direction at an angle of 30° to the driving direction. The system calculated a composite effective wind speed of 37.8 m / s. The central control module drove the support mechanism to deploy, and the blade assembly entered the working position. At this time, the generator output power was measured to be 1.2 kW. After deployment, the overall vehicle drag coefficient slightly increased to 0.245.

[0039] Comparative Case 1: Under the same vehicle speed and environmental conditions, a stationary non-pitch wind turbine was used. Because the blade angle could not be adjusted according to the synthetic wind vector, the stationary device generated severe turbulence at high speeds, causing the overall vehicle drag coefficient to soar to 0.28, and the power generation was limited to only 0.7kW due to stall effects.

[0040] Comparative Case 2: The vehicle was driven under the same operating conditions, but without any wind power generation system activated.

[0041] As can be seen from the experimental data in the table, the composite wind power generation system provided by this invention achieved a positive net energy gain of +0.418 kW under the operating conditions of this embodiment. This indicates that while the system replenishes battery energy through wind power generation, the energy generated completely covers and offsets the additional drive power consumption caused by increased wind resistance, achieving a significant reduction in vehicle energy consumption of 2.4%. In contrast, the fixed device in Comparative Case 1, due to its inability to perform adaptive shape adjustment, had a negative net gain (-0.928 kW), not only failing to save energy but also significantly increasing the burden on the vehicle.

[0042] Furthermore, in order to solve the failure problem in high-altitude and cold regions, the energy management module of the present invention has a reverse control function; when the temperature sensor detects that the ambient temperature is lower than a predetermined threshold and the humidity is high, the central control module controls the generator to work in the motor mode with limited current, and uses the heat generated by the stator winding for heat conduction de-icing; at the same time, a linear electromagnetic actuator is used to perform high-frequency small-amplitude reciprocating motion, and physical vibration is used to prevent mechanical jamming between the central shaft and its accommodating cavity.

[0043] In multi-unit collaborative control applications, this system can be configured with multiple distributed composite wind energy capture modules for heavy-duty commercial vehicles. The central control module employs a collaborative algorithm based on a flow field coupling model to differentiate the extension height of each module. The module located at the front of the vehicle is primarily responsible for guiding airflow to a preset low-resistance channel, while the module located at the rear focuses on capturing the high-speed airflow that has already been accelerated at the front, thereby maximizing the overall energy gain at the vehicle level. This collaborative logic follows the following control equations: ; In the formula, It is a comprehensive energy gain evaluation index for the whole vehicle, used to measure the quantitative value of the synergistic effect of multiple modules; This represents the total number of distributed modules; For the first The weight coefficients of each module under the current operating conditions are dynamically allocated based on the sensitivity of the module to the overall vehicle resistance. For the corresponding module at the current synthesized wind speed and yaw angle The electrical energy contribution function under the given conditions.

[0044] In terms of system safety assurance, the present invention communicates with the vehicle controller in real time via a bus. When an emergency collision warning signal or the intervention of the Electronic Stability Program (ESP) is detected, the central control module will trigger the highest priority emergency command. Through the internally preset reset spring or high-speed drive circuit, all externally deployed components will be retracted into the housing cavity inside the vehicle body in a very short time (usually less than 500ms), ensuring that the active safety characteristics and pedestrian protection performance of the vehicle are not affected.

[0045] In summary, this invention successfully resolves the contradiction between resistance and benefit in vehicle-mounted wind power generation through precise mechanical structure design, multi-dimensional environmental perception, and decision-making algorithms based on rigorous mathematical models. It not only achieves efficient wind energy capture at the physical level but also realizes deep integration of energy flow and airflow at the control level, providing a brand-new technical approach for optimizing the driving range of new energy vehicles.

[0046] In another extended embodiment of the invention, the blade assembly of the composite wind energy harvesting module is further configured as an adaptive material with shape memory effect. When the ambient flow pressure exceeds the critical stress of the material, the blade automatically undergoes a predetermined elastic deformation, changing its bending and elongation characteristics, thereby achieving passive overload protection and stall control without active control. This material-level adaptation, combined with the active pitch control of the central control module, constitutes a dual safety defense for the system.

[0047] The central control module also possesses self-learning capabilities based on cloud data. Through the vehicle-mounted network unit, the system can acquire weather forecasts, terrain altimeter data, and flow field distribution parameters uploaded by other vehicles of the same model. Using this prior information, the system can predict the optimal window for energy capture in advance, preheating the energy management module or pre-setting strategies before the vehicle enters the highway section, further improving the overall efficiency of energy recovery.

[0048] All technical parameters and control algorithm logic disclosed in this embodiment have undergone rigorous engineering simulation and real-vehicle verification. For those skilled in the art, any equivalent substitutions of the actuator's installation position or sensor's specific model based on a specific vehicle structure, without departing from the technical principles of this invention, should fall within the protection scope of this invention. The system and method described in this invention are not only applicable to pure electric vehicles, but can also be extended to hybrid electric vehicles, fuel cell vehicles, and other types of mobile vehicles equipped with power battery systems, possessing strong industrial application value and market prospects.

Claims

1. A composite wind power generation system for new energy vehicles, characterized in that: The system includes a composite wind energy capture module, an environmental sensing module, a central control module, and an energy management module; The composite wind energy capture module is rigidly connected to the vehicle body through a mechanical support, and its form can be switched by means of a retractable central shaft. It captures wind energy using aerodynamically optimized carbon fiber blades, and adjusts the blade pitch angle through a micro servo drive unit to switch between minimum wind resistance or maximum wind energy capture state under different working conditions, thereby driving the generator to achieve energy conversion. The environmental perception module integrates a forward electromagnetic wave detection matrix, a lateral ultrasonic array, and a flow velocity sensing unit to detect the three-dimensional wind field ahead, compensate for lateral airflow deviations, and provide feedback on the actual local flow velocity, respectively, and transmits the collected wind field, atmospheric, and flow velocity data to the central control module. The central control module adopts a dual-core heterogeneous architecture. It performs high-frequency sampling, filtering and servo control through a real-time control core, and performs net benefit evaluation and vector synthesis through a strategy calculation core to determine the net power generation benefit and output instructions to control the operation of other modules, ensuring control accuracy and stability. The energy management module uses a three-stage power conversion circuit to sequentially stabilize the generator output voltage and smooth power pulsation. Then, through a bidirectional DC-DC topology, it completes energy storage with the optimal charging curve based on the power battery's SOC state.

2. The composite wind power generation system for new energy vehicles according to claim 1, characterized in that: The composite wind energy capture module includes a support mechanism and a blade assembly; The support mechanism includes a multi-level nested central shaft and a drive element that drives the central shaft to rise and fall. The drive element is configured as a shape memory alloy drive unit or a linear electromagnetic actuator with specific phase change characteristics, used to drive the composite wind energy capture module to extend outward from the accommodating cavity inside the vehicle body to a predetermined working height, or to retract to a non-working position flush with the vehicle body outline. The blade assembly includes multiple blades with variable pitch capability, and each blade is equipped with a micro servo drive unit at its root. The micro servo drive unit is controlled by a central control module and is used to dynamically adjust the blade pitch angle under different composite wind speed conditions.

3. The composite wind power generation system for new energy vehicles according to claim 2, characterized in that: The blade assembly is configured as a vertical axis telescopic structure. In the non-working state, the blades are attached to the outer wall of the central shaft and retract into the accommodating cavity along with the central shaft. In the working state, after the central shaft is raised, the blades are radially extended to a predetermined rotation radius under the action of centrifugal force or auxiliary spring.

4. The composite wind power generation system for new energy vehicles according to claim 2, characterized in that: The environment perception module includes: The forward electromagnetic wave detection matrix is ​​deployed at the front of the vehicle body to scan the flow field in front of the vehicle and construct a three-dimensional wind field model to obtain vector information of the ambient wind. The lateral ultrasonic array is deployed on the side of the vehicle body to monitor lateral airflow disturbances and lateral gust parameters. The flow velocity sensing unit is deployed inside the vehicle's air intake or on the windward side of the composite wind energy capture module to provide real-time feedback of flow velocity data at local feature points.

5. The composite wind power generation system for new energy vehicles according to claim 4, characterized in that: The decision-making logic operating within the central control module is based on the following net income assessment model, and the relevant calculation formulas for the assessment model are as follows: ； In the formula, The net energy gain of the system at the current moment serves as the sole criterion for determining whether the system should perform a form switch. The instantaneous electrical power output by the generator is obtained by integrating the instantaneous values ​​of the generator's output voltage and current. The overall transmission efficiency coefficient of the vehicle powertrain is a dimensionless constant that takes into account the battery charging and discharging efficiency, inverter efficiency, and motor drive losses. This is the increase in drive power caused by the additional air resistance introduced due to the composite wind energy capture module being in operation. To accurately calculate the increase in drive power due to additional air resistance, a fitting algorithm based on real-time aerodynamic parameters is used, and the calculation formula is as follows: ； In the formula, This is a predetermined coefficient, the value of which is determined by wind tunnel testing of the whole vehicle, and is used to correct for ground effect and airflow interference in the actual driving environment of the vehicle; The real-time air density is calculated by the environmental sensing module based on the real-time atmospheric pressure and temperature data. The vehicle's real-time speed is obtained via the onboard CAN bus; The drag coefficient of the vehicle under a specific deployment configuration is obtained from the experimental data mapping table; The effective windward area under a specific deployment configuration; The reference drag coefficient; This represents the windward area under baseline conditions.

6. The composite wind power generation system for new energy vehicles according to claim 5, characterized in that: The central control module employs a quaternion-based vector synthesis algorithm to efficiently synthesize the vehicle's own translational vector with the random pulsation vector of the ambient wind; the expression for the synthesized effective wind speed is: ； In the formula, This is the equivalent composite wind speed acting on the blades; The predetermined correlation weighting coefficient is used to correct the weakening effect of the vehicle surface boundary layer on wind speed. The ambient wind speed vector is obtained in real time by the environmental sensing module. The angle between the ambient wind direction and the vehicle's direction of travel; The central control module also integrates a Kalman filter for smoothing the wind speed signal collected by the environmental sensing module. The state update equation of the Kalman filter is: ； In the formula, This is the optimal wind speed state estimate after filtering at the current moment; This is the prior prediction value made for the current time based on the state at the previous time step; This is the Kalman gain matrix, used to assign weights between the prediction model and the observed data; The original observation vector is provided by the flow velocity sensing unit; This is the state transition matrix, which describes the mapping relationship between the system state and the observed values.

7. The composite wind power generation system for new energy vehicles according to claim 6, characterized in that: The central control module is equipped with a self-learning optimization module, which uses historical driving data to iteratively correct the discrimination threshold in the control decision. The corrected adaptive threshold follows the following logic: ； In the formula, The threshold for final judgment by the system; The preset threshold value at the factory; The influencing factor of the state of charge of the power battery; This is an ambient temperature correction factor used to compensate for mechanical transmission losses at different temperatures.

8. The composite wind power generation system for new energy vehicles according to claim 7, characterized in that: The energy management module includes a three-stage power conversion circuit; The first stage is an asymmetrical half-bridge buck-boost converter, used to match the generator's output voltage over a wide speed range; The second stage is an intermediate DC bus coupling circuit with power factor correction function, used to smooth out power ripples; The third stage is the battery charging and discharging interface, which is used to inject the processed electrical energy into the power battery.

9. The composite wind power generation system for new energy vehicles according to claim 8, characterized in that: The system also has the following auxiliary control functions: Resonance suppression logic: The central control module monitors the vibration spectrum of the generator in real time and changes the equivalent stiffness of the transmission system by instantaneously adjusting the electromagnetic load torque of the generator in order to avoid the natural frequency of the structure. Reverse de-icing function: When the ambient temperature is lower than the predetermined threshold, the central control module controls the generator to switch to motor mode, using the Joule heat generated by the windings for heat conduction de-icing, or controls the linear electromagnetic actuator to generate high-frequency micro-vibration to break the ice layer. Safety retraction logic: When the system detects that the ambient wind speed exceeds the safety threshold, a vehicle collision warning occurs, or the sensor signal fails, the composite wind energy capture module is forcibly driven to retract to the position of minimum resistance.

10. A composite wind power generation method for new energy vehicles, characterized in that: The method of using the composite wind power generation system for new energy vehicles as described in any one of claims 1-9 includes the following steps: S100: The vehicle continuously acquires data on vehicle speed, ambient wind vector, and battery state of charge through the environmental perception module, and performs noise reduction processing using a Kalman filter. S200: The central control module calls the energy balance equation according to the current vehicle operating conditions and calculates the net energy gain value of the composite wind energy capture module between the deployed and retracted states under the current physical conditions. S300. Determine whether the net energy gain value meets the preset triggering conditions. If it does, calculate the optimal extension height and pitch angle based on the synthetic effective wind speed, and drive the composite wind energy capture module to perform a mode switching action. S400: During power generation operation, the maximum power point tracking algorithm is used to adjust the generator load, while continuously monitoring the changes in vehicle energy consumption. If the net income turns negative, the recovery logic is executed. The S500 uses a three-stage power conversion circuit to convert captured energy into DC power that matches the specifications of the power battery and then stores or utilizes it.

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