New energy vehicle intelligent energy recovery system and control method thereof

Abstract

The application discloses a new energy automobile intelligent energy recovery system and a control method thereof. The system comprises a vehicle running state acquisition module, a battery state monitoring module, an energy recovery control unit and a driving execution unit. The vehicle running state acquisition module is used for acquiring the speed, acceleration and brake pedal position information of the vehicle in real time; the battery state monitoring module is used for detecting the voltage, current, temperature and state of charge of the battery; the energy recovery control unit dynamically calculates the optimal energy recovery intensity and timing based on an intelligent algorithm and in combination with preset working condition parameters in an energy recovery strategy module, and outputs a control instruction to the driving execution unit; and the driving execution unit converts the kinetic energy of the vehicle into electric energy and feeds back to the battery in the braking stage, so that the real-time optimization of the energy recovery process is realized.

Description

Technical Field

[0001] This invention belongs to the field of new energy vehicle technology. Specifically, this invention relates to an intelligent energy recovery system for new energy vehicles and its control method. Background Technology

[0002] With the escalating global energy crisis and increasingly prominent environmental pollution problems, new energy vehicles, as a green and environmentally friendly mode of transportation, have received widespread attention. New energy vehicles primarily rely on batteries as their power source, and their energy utilization efficiency directly affects the vehicle's range and operating costs. During the operation of new energy vehicles, the regenerative braking system (RBS) is one of the key technologies for improving energy utilization efficiency.

[0003] Existing regenerative braking systems primarily recover and reuse energy by converting the vehicle's kinetic energy into electrical energy during braking and storing it in the battery. However, existing technologies have some shortcomings. For example, traditional regenerative braking systems have low recovery efficiency and are not intelligent enough to dynamically adjust based on the vehicle's actual operating conditions and battery status. Furthermore, existing systems may overcharge the battery during energy recovery, affecting its lifespan.

[0004] Existing regenerative braking systems suffer from the following main problems: First, their recovery efficiency is low, failing to fully utilize the energy generated during vehicle braking; second, they lack intelligent control, unable to dynamically adjust based on the vehicle's actual operating status and battery condition; and third, they may overcharge the battery, affecting its lifespan. These problems limit further improvements in the energy utilization efficiency of new energy vehicles, and also impact vehicle range and operating costs.

[0005] This invention provides an intelligent energy recovery system for new energy vehicles, with a particular focus on how to improve energy recovery efficiency. Summary of the Invention

[0006] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention provides an intelligent energy recovery system for new energy vehicles, with the purpose of improving energy recovery efficiency.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: an intelligent energy recovery system for new energy vehicles, comprising: The vehicle status acquisition module is used to acquire real-time vehicle operating status information, including vehicle speed, acceleration, and braking signals. The battery management module is used to monitor the battery's voltage, current, temperature, and state of charge. An energy recovery control module, communicatively connected to the vehicle status acquisition module and the battery management module, is used to dynamically determine the intensity and timing of energy recovery based on the vehicle's operating status and the battery status using an intelligent control algorithm; and The drive motor operates in generator mode under braking conditions according to the instructions of the energy recovery control module, converting the vehicle's kinetic energy into electrical energy and inputting it into the battery. The energy recovery control module performs closed-loop adjustment of the energy recovery intensity based on real-time changes in vehicle operating status and battery status, so as to improve energy recovery efficiency and vehicle range while avoiding overcharging of the battery.

[0008] The intelligent control algorithm calculates the optimal energy recovery intensity based on the comprehensive parameters of vehicle speed, acceleration, braking signal and battery SOC, and makes real-time corrections according to the preset energy recovery strategy.

[0009] The energy recovery control module includes: The intelligent algorithm unit is used to calculate the optimal energy recovery intensity and timing; The intensity adjustment unit is used to output control commands to the drive motor to adjust the speed and braking torque; The status monitoring unit is used to receive real-time information from the vehicle status acquisition module and the battery management module.

[0010] The energy recovery control module communicates with the drive motor via CAN bus or Ethernet to achieve high-speed data interaction and control signal synchronization.

[0011] The intelligent control algorithm adopts an algorithm model based on neural networks or fuzzy control, which is used to achieve adaptive energy recovery optimization by learning vehicle operation data.

[0012] The vehicle status acquisition module includes a speed sensor, an acceleration sensor, and a brake pedal position sensor, which work together to determine the driver's braking intention.

[0013] The vehicle status acquisition module includes a vision sensor for identifying the vehicle's surrounding environment and dynamic features to help determine braking status and recovery intensity.

[0014] The battery management module includes a voltage sampling unit, a current sampling unit, a temperature detection unit, and a SOC calculation unit. Each unit outputs filtered monitoring data.

[0015] The drive motor is a permanent magnet synchronous motor, a switched reluctance motor, or an asynchronous motor.

[0016] The present invention also provides a method for intelligent energy recovery control of new energy vehicles based on the system, comprising the following steps: Collect vehicle operating status information and battery status information; Determine if the vehicle is braking; When the vehicle brakes, an intelligent algorithm is executed to calculate the optimal energy recovery intensity and timing based on the real-time operating status and battery status. Output control commands to the drive motor to perform energy recovery; It continuously receives feedback information from the vehicle and battery, dynamically adjusts the energy recovery control parameters, and achieves closed-loop optimization of energy recovery.

[0017] The energy recovery control module automatically reduces the energy recovery intensity when it receives a battery SOC higher than a set threshold, in order to avoid overcharging the battery.

[0018] The intelligent energy recovery system for new energy vehicles of the present invention has the following beneficial effects: 1. Improve energy recovery efficiency: Through intelligent control algorithms, this invention can dynamically adjust the intensity and timing of energy recovery according to the actual operating status of the vehicle and the battery status, thereby maximizing the recovery of energy generated during vehicle braking and improving energy utilization efficiency.

[0019] 2. Extend battery life: The energy recovery control module of this invention can monitor the battery status in real time, avoid overcharging the battery, and thus extend the battery life.

[0020] 3. Improve vehicle range: By improving energy recovery efficiency and extending battery life, this invention can effectively improve the range of new energy vehicles and reduce operating costs.

[0021] 4. Enhanced driving experience: The energy recovery system of this invention can dynamically adjust the intensity of energy recovery according to the actual operating status of the vehicle, making the deceleration of the vehicle during braking smoother and enhancing the driving experience. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the intelligent energy recovery system for new energy vehicles of the present invention; Figure 2 This is a control flowchart of the intelligent energy recovery system for new energy vehicles of the present invention; Figure 3 This is a schematic diagram of the intelligent algorithm of the energy recovery controller of the present invention; Figure 4 It is a diagram showing the vehicle's operating status information, such as speed, acceleration, and brake pedal position, as well as the battery's status information, such as voltage, current, temperature, and SOC. Figure 5 It is a diagram showing the intensity and timing of energy recovery; The markings in the above diagrams are: 1. Main reducer; 2. Drive motor; 3. Inverter; 4. Battery; 5. Regenerative braking controller; 6. Vehicle controller; 7. Pressure regulator. Detailed Implementation

[0023] To facilitate understanding of the present invention, a more comprehensive description of the present invention will be given below with reference to the accompanying drawings, which illustrate several embodiments of the present invention. However, the present invention can be implemented in different forms and is not limited to the embodiments described in the text. Rather, these embodiments are provided to make the disclosure of the present invention more thorough and complete.

[0024] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "upper," "lower," and similar expressions used in this document are for illustrative purposes only.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly associated with those skilled in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments and is not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0026] Firstly, such as Figure 1 As shown, this embodiment of the invention provides an intelligent energy recovery system for new energy vehicles, comprising: The vehicle status acquisition module is used to acquire real-time vehicle operating status information, including vehicle speed, acceleration, and braking signals. The battery management module is used to monitor the battery's voltage, current, temperature, and state of charge. The energy recovery control module communicates with the vehicle status acquisition module and the battery management module, and is used to dynamically determine the intensity and timing of energy recovery based on the vehicle's operating status and battery status using intelligent control algorithms; and The drive motor operates in generator mode under braking conditions, according to the instructions of the energy recovery control module, converting the vehicle's kinetic energy into electrical energy and inputting it into the battery.

[0027] Specifically, this invention aims to solve the problems of low recovery efficiency, lack of intelligent control, and potential overcharging of batteries in existing regenerative braking systems for new energy vehicles. It provides an intelligent energy recovery system and its control method to improve the energy utilization efficiency and driving range of new energy vehicles, while extending the battery's lifespan.

[0028] This invention proposes an intelligent energy recovery system for new energy vehicles, the core of which lies in dynamically optimizing the energy recovery process through intelligent control algorithms. The system includes a vehicle status acquisition module, a battery management module, an energy recovery control module, and a drive motor. The vehicle status acquisition module monitors the vehicle's operating status information in real time, such as speed, acceleration, and brake pedal position; the battery management module monitors parameters such as battery voltage, current, temperature, and state of charge (SOC); the energy recovery control module dynamically adjusts the intensity and timing of energy recovery based on the vehicle's operating status and battery status using intelligent algorithms; and the drive motor acts as a generator during braking, converting the vehicle's kinetic energy into electrical energy and storing it in the battery.

[0029] The energy recovery system of this invention is achieved through the following technical solution: 1. The vehicle status acquisition module collects real-time operating status information such as vehicle speed, acceleration, and brake pedal position, and transmits it to the energy recovery controller.

[0030] 2. The battery management module monitors parameters such as battery voltage, current, temperature, and state of charge (SOC) in real time and feeds this information back to the energy recovery controller.

[0031] 3. The energy recovery control module dynamically adjusts the intensity and timing of energy recovery based on the vehicle's operating status and battery status using an intelligent algorithm. This intelligent algorithm calculates the optimal energy recovery intensity and timing based on the vehicle's real-time operating status and battery status, combined with a preset energy recovery strategy.

[0032] 4. During braking, the drive motor acts as a generator, converting the vehicle's kinetic energy into electrical energy and storing it in the battery according to the instructions of the energy recovery control module. Simultaneously, the energy recovery control module precisely controls the energy recovery process by adjusting the drive motor's speed and torque.

[0033] In this embodiment of the invention, the intelligent control algorithm calculates the optimal energy recovery intensity based on comprehensive parameters including vehicle speed, acceleration, braking signal, and battery SOC, and makes real-time corrections according to a preset energy recovery strategy. The intelligent control algorithm employs an algorithm model based on neural networks or fuzzy control to achieve adaptive energy recovery optimization by learning vehicle operating data.

[0034] like Figure 1 and Figure 2As shown, the new energy vehicle is equipped with an inverter, a vehicle controller and a regenerative braking controller. The inverter is electrically connected to the battery and the drive motor. The drive motor is connected to the drive shaft through the transmission system. The drive shaft is connected to the two first wheels. The power generated by the drive motor is transmitted to the two first wheels through the transmission system and the drive shaft. The first wheels are the front wheels of the vehicle.

[0035] like Figure 1 As shown, the intelligent energy recovery system for new energy vehicles of the present invention includes a vehicle status acquisition module, a battery management module, an energy recovery control module, and a drive motor. The vehicle status acquisition module is used to monitor the vehicle's operating status information in real time, such as speed, acceleration, and brake pedal position; the battery management module is used to monitor parameters such as battery voltage, current, temperature, and state of charge (SOC); the energy recovery control module dynamically adjusts the intensity and timing of energy recovery based on the vehicle's operating status and battery status through intelligent algorithms; the drive motor acts as a generator during braking, converting the vehicle's kinetic energy into electrical energy and storing it in the battery.

[0036] In this embodiment of the invention, the vehicle status acquisition module includes a speed sensor, an acceleration sensor, and a brake pedal position sensor, which work together to determine the driver's braking intention. The speed sensor monitors the vehicle's speed information in real time; the acceleration sensor monitors the vehicle's acceleration information in real time; and the brake pedal position sensor monitors the brake pedal position information in real time. These sensors transmit the collected information to the energy recovery control module, providing the energy recovery control module with real-time vehicle operating status information.

[0037] In this embodiment of the invention, the vehicle status acquisition module may further include a vision sensor for identifying the vehicle's surrounding environment and dynamic characteristics to assist in determining braking status and regenerative braking intensity. The vision sensor can acquire and analyze images of the vehicle's surrounding environment to obtain real-time information such as vehicle speed, acceleration, and braking status. Compared to traditional sensors, vision sensors offer advantages such as non-contact measurement and rich information, providing more comprehensive vehicle operating status information and more accurate input data for the energy recovery controller.

[0038] In this embodiment of the invention, the energy recovery control module performs closed-loop adjustment of the energy recovery intensity based on real-time changes in vehicle operating status and battery status, thereby improving energy recovery efficiency and vehicle range while avoiding overcharging of the battery. The energy recovery control module includes: The intelligent algorithm unit is used to calculate the optimal energy recovery intensity and timing; The intensity adjustment unit is used to output control commands to the drive motor to adjust the speed and braking torque; The status monitoring unit is used to receive real-time information from the vehicle status acquisition module and the battery management module.

[0039] In this embodiment of the invention, the energy recovery control module further includes a braking signal input module, a battery status monitoring module, and an energy recovery strategy module. The battery status monitoring module receives battery status information from the battery management module. The braking signal input module receives braking signals from the brake pedal position sensor.

[0040] The intelligent algorithm unit calculates the optimal energy recovery intensity and timing based on the vehicle's operating status and battery status, combined with the preset strategies in the energy recovery strategy module, and sends control commands to the drive motor through the intensity adjustment module.

[0041] During braking, the drive motor acts as a generator, converting the vehicle's kinetic energy into electrical energy and storing it in the battery, according to instructions from the energy recovery control module. Simultaneously, the energy recovery control module precisely controls the energy recovery process by adjusting the drive motor's speed and torque.

[0042] In this embodiment of the invention, the energy recovery control module communicates with the drive motor via CAN bus or Ethernet to achieve high-speed data interaction and control signal synchronization.

[0043] In this embodiment of the invention, the control algorithm principle adopted by the intelligent algorithm unit in the energy recovery control module is as follows: Figure 3 As shown. This algorithm dynamically calculates the optimal energy recovery intensity and timing based on the vehicle's real-time operating status and battery status, combined with a preset energy recovery strategy. Specifically, the intelligent algorithm unit performs calculations based on the following factors: 1. Vehicle Speed ​​and Acceleration: Vehicle speed and acceleration are important factors affecting the intensity of energy recovery. When the vehicle speed is high and the acceleration is negative, it indicates that the vehicle is in a high-speed braking state. At this time, the energy recovery intensity should be appropriately increased to make full use of the vehicle's kinetic energy. Conversely, when the vehicle speed is low and the acceleration is negative, the energy recovery intensity should be appropriately reduced to avoid excessively affecting the vehicle's braking performance.

[0044] 2. Brake Pedal Position: The position of the brake pedal reflects the driver's braking intention. When the brake pedal is pressed deeper, it indicates that the driver needs greater braking force, and the energy recovery intensity should be appropriately increased; when the brake pedal is pressed shallower, the energy recovery intensity should be appropriately reduced.

[0045] 3. Battery State: Battery voltage, current, temperature, and state of charge (SOC) are crucial factors affecting energy recovery. A low SOC indicates the battery requires more energy, thus the energy recovery intensity should be increased appropriately. Conversely, a high SOC requires a decrease in energy recovery intensity to avoid overcharging. Battery temperature also affects the energy recovery process. Excessively high battery temperatures necessitate a reduction in energy recovery intensity to prevent overheating.

[0046] 4. Energy Recovery Strategy: The energy recovery strategy module has different preset energy recovery strategies. Based on the vehicle's actual operating conditions and battery status, the intelligent algorithm unit selects the optimal energy recovery strategy. For example, in urban conditions, where the vehicle frequently starts and stops, the energy recovery strategy should focus on improving energy recovery efficiency; in high-speed conditions, where the vehicle brakes less frequently, the energy recovery strategy should focus on balancing energy recovery efficiency and vehicle braking performance.

[0047] Through the aforementioned intelligent algorithm, this invention can achieve dynamic optimization of the energy recovery process, improve energy recovery efficiency, extend battery life, and enhance vehicle range and driving experience.

[0048] During vehicle operation, the vehicle sensor module monitors vehicle speed, acceleration, and brake pedal position in real time, and transmits the data to the vehicle operating status monitoring module of the energy recovery controller. The battery management system monitors battery voltage, current, temperature, and state of charge (SOC) in real time, and transmits the data to the battery status monitoring module of the controller. The brake signal input module synchronously receives signals from the brake pedal sensor to determine whether the vehicle has entered a braking state; if it is in a braking state, it triggers the intelligent algorithm unit to start calculations.

[0049] In this embodiment of the invention, the battery management module includes a voltage sampling unit, a current sampling unit, a temperature detection unit, and a SOC calculation unit. Each unit outputs filtered monitoring data. The voltage sampling unit is a voltage sensor used to monitor the battery's voltage information in real time. The current sampling unit is a current sensor used to monitor the battery's current information in real time. The temperature detection unit is a temperature sensor used to monitor the battery's temperature information in real time. The SOC calculation unit is used to monitor the battery's state of charge in real time. These monitoring modules transmit the collected information to the energy recovery control module, providing the energy recovery control module with real-time battery status information.

[0050] In this embodiment of the invention, the energy recovery control module can be implemented using different hardware architectures and software algorithms. For example, a hardware architecture based on an FPGA (Field-Programmable Gate Array) can be used, combined with a neural network algorithm to dynamically optimize the energy recovery process. The FPGA has high-speed parallel processing capabilities, enabling rapid response to vehicle braking signals and battery state changes, improving the real-time performance and accuracy of energy recovery. The neural network algorithm can automatically adjust the energy recovery strategy by learning from a large amount of vehicle operating data and battery state data, further improving energy recovery efficiency.

[0051] In this embodiment of the invention, the drive motor can be a permanent magnet synchronous motor, a switched reluctance motor, or an asynchronous motor. Switched reluctance motors offer high efficiency, high power density, and good speed regulation performance, enabling them to quickly respond to the energy recovery controller's commands during braking, thus improving energy recovery efficiency. Asynchronous motors, on the other hand, have the advantages of simple structure, low cost, and high reliability, making them suitable for cost-sensitive new energy vehicle applications.

[0052] In this embodiment of the invention, the battery management module is used to monitor parameters such as battery voltage, current, temperature, and SOC. Besides using a traditional battery management system, a battery management system based on a wireless sensor network can also be employed. The wireless sensor network enables real-time monitoring and data transmission of battery status without the need for complex wiring, reducing system complexity and cost. Furthermore, the wireless sensor network can be flexibly deployed at different locations within the battery pack, improving the accuracy and reliability of battery status monitoring.

[0053] Secondly, embodiments of the present invention also provide a system-based intelligent energy recovery control method for new energy vehicles, comprising the following steps: S1. Collect vehicle operating status information and battery status information; S2. Determine if the vehicle is in a braking state; S3. When the vehicle brakes, an intelligent algorithm is executed to calculate the optimal energy recovery intensity and timing based on the real-time operating status and battery status. S4. Output control commands to the drive motor to perform energy recovery; S5 continuously receives feedback information from the vehicle and battery, dynamically corrects energy recovery control parameters, and achieves closed-loop optimization of energy recovery.

[0054] In step S1 above, the vehicle status acquisition module monitors the vehicle's speed, acceleration, brake pedal position, and other operating status information in real time and transmits this information to the energy recovery control module. The battery management module monitors the battery's voltage, current, temperature, and state of charge (SOC) parameters in real time and feeds this information back to the energy recovery control module.

[0055] In step S2 above, the brake signal input module in the energy recovery control module receives the brake signal from the brake pedal position sensor and determines whether the vehicle is in a braking state.

[0056] In step S3 above, when the vehicle is braking, the intelligent algorithm unit in the energy recovery control module calculates the optimal energy recovery intensity and timing based on the vehicle's operating status and battery status, combined with the preset strategy in the energy recovery strategy module. The energy recovery intensity adjustment unit in the energy recovery control module then sends control commands to the drive motor based on the calculation results from the intelligent algorithm unit, adjusting the drive motor's speed and torque to achieve precise control of the energy recovery process.

[0057] like Figure 3 As shown, step S3 above includes: S301, Solve for the total braking force; S302, Front and rear wheel brake force distribution; S303, Motor braking and coordinated braking triggering.

[0058] In step S301 above, the intelligent algorithm unit first calculates the total braking force required by the vehicle based on the brake pedal position (reflecting the driver's braking intention), vehicle speed, and acceleration. The total braking force must meet the driver's deceleration needs. For example, the deeper the brake pedal is positioned and the higher the vehicle speed, the greater the total braking force required.

[0059] In step S302 above, according to vehicle braking safety rules, the total braking force is divided into front wheel braking force distributed to the front wheels and rear wheel mechanical braking force distributed to the rear wheels. The rear wheels rely solely on the brakes for mechanical braking, while the front wheels can be braked in conjunction with the electric motor, preventing wheel lock-up or fishtailing during braking and ensuring braking stability. The braking force of the drive motor is the core of energy recovery; the motor reverses to generate braking force, thus achieving energy recovery.

[0060] In step S303 above, if Z≤0.1, the drive motor directly provides all the braking force to the front wheels, and the mechanical braking force generated by the brakes installed on the front wheels is 0, so the brakes do not work. Z is the braking safety threshold, which is triggered when the braking force distribution approaches the threshold.

[0061] In step S303 above, if Z > 0.1, coordinated braking is triggered to synchronize and coordinate the response speeds of motor braking and mechanical braking, avoiding unstable deceleration caused by fluctuations in braking force. At this time, it is necessary to calculate the maximum braking force F_ems of the drive motor and the required braking force Fq_req of the front wheels. The maximum braking force of the drive motor is limited by the motor speed, torque limit, and battery charging capacity. The required braking force Fq_req of the front wheels is the actual braking force required by the front wheels, which is allocated from the total braking force.

[0062] In step S303 above, if the maximum braking force F_ems of the drive motor is greater than or equal to the braking force required by the front wheels Fq_req, then the drive motor directly provides all the braking force of the front wheels. The mechanical braking force generated by the brakes installed on the front wheels is 0, and the brakes do not work. At this time, the energy recovery intensity is maximized, and kinetic energy is used to generate electricity first.

[0063] If the maximum braking force of the drive motor F_ems is less than the required braking force of the front wheels Fq_req, then while the drive motor provides the maximum braking force, the mechanical braking force generated by the brakes on the front wheels will be activated to supplement the braking force. The mechanical braking force of the front wheels = the required braking force of the front wheels - the maximum braking force of the motor.

[0064] Through a two-layer control logic that combines safety threshold judgment and motor capacity matching judgment, a balance is achieved between braking safety and energy recovery efficiency. Priority is given to using motor braking to recover energy and maximize recovery efficiency. When the motor capacity is insufficient or the safety conditions are not met, mechanical braking is used to supplement it and ensure braking performance. The coordinated braking link avoids sudden changes in braking force and improves driving smoothness.

[0065] In step S4 above, the drive motor acts as a generator during vehicle braking, generating electricity and converting the vehicle's kinetic energy into electrical energy according to the instructions of the energy recovery control module, and storing it in the battery.

[0066] Figure 4 (The input data for this example) is the real-time input to the algorithm. Figure 5 (The output data of the example) is the calculation result of the algorithm. The time-series correspondence between the two reflects how the algorithm transforms dynamic data into recycling parameters. The specific process is as follows: 1. Input data substitution: The algorithm will... Figure 4 The parameters at each time point (e.g., at t=0: vehicle speed is 40km / h, vehicle acceleration is -2m / s², brake pedal opening is 30%, and SOC is 60%) are substituted into the core decision-making logic and combined with the preset energy recovery strategy.

[0067] Vehicle parameters affect: When t=0, the vehicle speed is high and the acceleration is negative. At this time, high-speed braking is possible, and the algorithm can determine to increase the recovery intensity. When the brake pedal position is 30%, it is in shallow braking, and the recovery intensity needs to be moderate to avoid affecting the braking feel.

[0068] Battery parameters affect the following: At t=0, with an SOC of 60% and a temperature of 25℃, the algorithm determines that the battery is ready for charging and there is no need to reduce the recycling intensity.

[0069] 2. Output recovery parameters: The algorithm considers the above factors to calculate the energy recovery intensity and timing at each time point. When t=0: After comprehensive judgment, the output recovery intensity is 30% and the timing is 0.1s, that is, energy recovery starts 0.1s after braking begins, to avoid sudden changes in braking force in the early stage of braking.

[0070] Timing adjustment: As time progresses (t=1 to t=4), the brake pedal position increases from 30% to 70% (increased braking intent), the SOC increases from 60% to 70%, the battery is still rechargeable, the algorithm gradually increases the recovery intensity from 30% to 50%, and the timing of energy recovery is delayed from 0.1s after braking begins to 0.5s to adapt to the increased braking depth requirements.

[0071] like Figure 4 and Figure 5 As shown, when the vehicle speed is high, such as 40km / h, and the acceleration is negative, such as -2m / s², that is, during high-speed braking, the total amount of recoverable kinetic energy is large. The algorithm will appropriately increase the recovery intensity to fully capture the kinetic energy. At the same time, because the kinetic energy decays quickly during high-speed braking, the recovery timing needs to be advanced, such as starting energy recovery 0.1s after the start of braking, to avoid wasting kinetic energy.

[0072] like Figure 4 and Figure 5 As shown, when the vehicle speed is low, such as 20km / h, and the acceleration is negative, such as -0.5m / s², that is, when braking at low speed, there is little kinetic energy that can be recovered, and excessive recovery can easily lead to braking jerking. The algorithm will appropriately reduce the recovery intensity, and the recovery timing can also be delayed, such as starting energy recovery 0.5s after braking begins, to prioritize ensuring braking smoothness.

[0073] like Figure 4 and Figure 5 As shown, when the brake pedal is in a deeper position, such as 70%, it indicates that the driver needs to force the brakes. The algorithm will increase the regenerative braking intensity. At this time, the electric motor power can assist in enhancing the total braking force, and the timing of regenerative braking is advanced in sync with the braking action, balancing efficiency and braking needs.

[0074] When the brake pedal is at a shallow position, such as 30%, it indicates that the driver only needs to decelerate gently. The algorithm will reduce the intensity of regenerative braking to avoid excessive regenerative force that could cause abrupt deceleration.

[0075] like Figure 4 and Figure 5 As shown, when the battery's SOC is low, such as 60%, the battery still has considerable charging potential, and the algorithm will increase the recycling intensity, allowing more kinetic energy to be converted into electrical energy for storage. When the battery's SOC is high, such as above 90%, the battery is close to full charge, and continuing high-intensity recycling can easily lead to overcharging. In this case, the algorithm will significantly reduce the recycling intensity or even stop recycling to protect the battery's lifespan.

[0076] In urban driving conditions, the preset strategy prioritizes improving energy recovery efficiency. The algorithm is more sensitive to brake pedal action, initiating recovery even with light braking, and adjusting the recovery intensity more frequently to maximize the capture of kinetic energy from frequent braking.

[0077] like Figure 4 and Figure 5 As shown, under urban driving conditions, within the braking initiation time t=0 to t=4 seconds, that is, within the time from 0 seconds to 4 seconds after braking begins, the vehicle frequently decelerates, with the speed decreasing from 40km / h to 20km / h. The algorithm, combined with the preset strategy of prioritizing urban efficiency, gradually increases the recovery intensity from 30% to 70% as the brake pedal position deepens, and the SOC gradually increases from 60% to 70%, gradually increasing the recovery intensity from 30% to 50%, while delaying the timing from 0.1s to 0.5s. This approach not only fully recovers kinetic energy but also adapts to the enhanced braking intent.

[0078] In this embodiment, the energy recovery control module dynamically adjusts the intensity and timing of energy recovery based on the vehicle's real-time operating status and battery status.

[0079] For example, at the 0th second of braking initiation, the vehicle speed is 40 km / h, the acceleration is -2 m / s², the brake pedal position is 30%, the battery voltage is 300 V, the battery current is 50 A, the battery temperature is 25℃, and the battery SOC is 60%. At this time, the intelligent algorithm unit calculates an energy recovery intensity of 30% and an energy recovery timing of 0.1 seconds. The energy recovery control module sends control commands to the drive motor through the energy recovery intensity adjustment module, adjusting the drive motor's speed and torque so that the vehicle converts some kinetic energy into electrical energy and stores it in the battery during braking. In subsequent braking processes, the energy recovery control module dynamically adjusts the intensity and timing of energy recovery based on real-time monitoring of the vehicle's operating status and battery status to ensure optimal energy recovery performance.

[0080] For example, in the first second of braking, the vehicle speed is 35 km / h, the acceleration is -1.5 m / s², the brake pedal position is 40%, the battery voltage is 302 V, the battery current is 45 A, the battery temperature is 26℃, and the battery SOC is 62%. At this time, the intelligent algorithm unit calculates the energy recovery intensity as 35% and the energy recovery timing as 0.2 seconds.

[0081] For example, at the second second after braking begins, the vehicle speed is 30 km / h, the acceleration is -1 m / s², the brake pedal position is 50%, the battery voltage is 305 V, the battery current is 40 A, the battery temperature is 27°C, and the battery SOC is 65%. At this time, the intelligent algorithm unit calculates the energy recovery intensity as 40% and the energy recovery timing as 0.3 seconds.

[0082] For example, at the 3rd second after braking begins, the vehicle speed is 25 km / h, the acceleration is -0.5 m / s², the brake pedal position is 60%, the battery voltage is 308 V, the battery current is 35 A, the battery temperature is 28 °C, and the battery SOC is 68%. At this time, the intelligent algorithm unit calculates the energy recovery intensity as 45% and the energy recovery timing as 0.4 seconds.

[0083] For example, at the 4th second after braking is initiated, the vehicle speed is 20 km / h, the acceleration is 0 m / s², the brake pedal position is 70%, the battery voltage is 310 V, the battery current is 30 A, the battery temperature is 29 °C, and the battery SOC is 70%. At this time, the intelligent algorithm unit calculates the energy recovery intensity as 50% and the energy recovery timing as 0.5 seconds.

[0084] Under high-speed conditions, the number of braking operations is less. The preset strategy prioritizes balancing recovery efficiency and braking performance. The algorithm only increases the recovery intensity during deep braking, and the timing control is more cautious to avoid fluctuations in recovery force during high-speed braking affecting driving stability and to prevent sacrificing safety for the sake of efficiency.

[0085] In step S5 above, during the energy recovery process, the vehicle status acquisition module and the battery management module continuously monitor the vehicle's operating status and battery status, and feed back real-time information to the energy recovery control module. Based on the real-time feedback information, the energy recovery control module dynamically adjusts the intensity and timing of energy recovery to ensure optimal performance of the energy recovery process.

[0086] When the brake pedal is reset (indicating the end of braking) or the battery SOC reaches 90% or higher, the algorithm terminates energy recovery to ensure battery safety matches driving needs.

[0087] In this embodiment of the invention, the energy recovery control module automatically reduces the energy recovery intensity when it receives a battery SOC higher than a set threshold, so as to avoid overcharging the battery.

[0088] The intelligent energy recovery system and control method for new energy vehicles of this invention significantly improve the energy recovery efficiency of the vehicle when driving on urban roads, extend the battery life, and increase the vehicle's driving range. Furthermore, due to the more intelligent energy recovery process, the vehicle decelerates more smoothly during braking, improving the driving experience.

[0089] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution of the present invention, or the direct application of the inventive concept and technical solution of the present invention to other occasions without modification, are all within the protection scope of the present invention.

Claims

1. A smart energy recovery system for new energy vehicles, characterized in that, include: The vehicle status acquisition module is used to acquire real-time vehicle operating status information, including vehicle speed, acceleration, and braking signals. The battery management module is used to monitor the battery's voltage, current, temperature, and state of charge. The energy recovery control module is communicatively connected to the vehicle status acquisition module and the battery management module, and is used to dynamically determine the energy recovery intensity and timing based on the vehicle operating status and battery status through an intelligent control algorithm. as well as The drive motor operates in generator mode under braking conditions according to the instructions of the energy recovery control module, converting the vehicle's kinetic energy into electrical energy and inputting it into the battery. The energy recovery control module performs closed-loop adjustment of the energy recovery intensity based on real-time changes in the vehicle's operating status and the battery's status.

2. The intelligent energy recovery system for new energy vehicles according to claim 1, characterized in that, The intelligent control algorithm calculates the optimal energy recovery intensity based on the comprehensive parameters of vehicle speed, acceleration, braking signal and battery SOC, and makes real-time corrections according to the preset energy recovery strategy.

3. The intelligent energy recovery system for new energy vehicles according to claim 1 or 2, characterized in that, The energy recovery control module includes: The intelligent algorithm unit is used to calculate the optimal energy recovery intensity and timing; The intensity adjustment unit is used to output control commands to the drive motor to adjust the speed and braking torque; The status monitoring unit is used to receive real-time information from the vehicle status acquisition module and the battery management module.

4. The intelligent energy recovery system for new energy vehicles according to any one of claims 1 to 3, characterized in that, The intelligent control algorithm adopts an algorithm model based on neural networks or fuzzy control, which is used to achieve adaptive energy recovery optimization by learning vehicle operation data.

5. The intelligent energy recovery system for new energy vehicles according to any one of claims 1 to 4, characterized in that, The vehicle status acquisition module includes a speed sensor, an acceleration sensor, and a brake pedal position sensor, which work together to determine the driver's braking intention.

6. The intelligent energy recovery system for new energy vehicles according to claim 5, characterized in that, The vehicle status acquisition module includes a vision sensor for identifying the vehicle's surrounding environment and dynamic features to help determine braking status and recovery intensity.

7. The intelligent energy recovery system for new energy vehicles according to any one of claims 1 to 5, characterized in that, The battery management module includes a voltage sampling unit, a current sampling unit, a temperature detection unit, and a SOC calculation unit. Each unit outputs filtered monitoring data.

8. The intelligent energy recovery system for new energy vehicles according to any one of claims 1 to 5, characterized in that, The drive motor is a permanent magnet synchronous motor, a switched reluctance motor, or an asynchronous motor.

9. A method for intelligent energy recovery control of new energy vehicles based on the system described in any one of claims 1 to 8, characterized in that, Includes the following steps: Collect vehicle operating status information and battery status information; Determine if the vehicle is braking; When the vehicle brakes, an intelligent algorithm is executed to calculate the optimal energy recovery intensity and timing based on the real-time operating status and battery status. Output control commands to the drive motor to perform energy recovery; It continuously receives feedback information from the vehicle and battery, dynamically adjusts the energy recovery control parameters, and achieves closed-loop optimization of energy recovery.

10. The method according to claim 9, characterized in that, The energy recovery control module automatically reduces the energy recovery intensity when it receives a battery SOC higher than a set threshold, in order to avoid overcharging the battery.

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