Dynamic power distribution control method for three-power collaborative optimization of new energy automobile

Abstract

The invention discloses a dynamic power distribution control method for three-power collaborative optimization of a new energy automobile, and relates to the technical field of new energy automobiles. According to the battery management system, the discharging strategy of the battery is adjusted according to the requirement of the electric control system so as to provide stable and efficient energy output, the battery management system is also responsible for adopting a charging strategy in the battery charging process so as to prevent the over-charging or over-discharging phenomenon, and the service life of the battery can be prolonged; the electric control system collects dynamic data of the vehicle in real time based on a sensor unit arranged in the vehicle and rapidly processes and analyzes the data, the power output of a motor is dynamically adjusted according to the state of the vehicle and road conditions, and the cooperative system provides a safety threshold and efficiency optimization suggestion based on the battery management system and the electric control system. And stable operation of the three-electricity system is ensured.

Description

Technical Field

[0001] The present invention relates to the field of new energy vehicle technology, and in particular to a dynamic power distribution control method for coordinated optimization of three-electric systems in a new energy vehicle. Background Art

[0002] New energy vehicles (NEVs) use unconventional fuels as their power source (or use conventional fuels with new onboard power units), integrating advanced technologies in vehicle power control and drive to create vehicles with advanced technical principles, new technologies, and new structures. New energy vehicles include gas-fired vehicles, hybrid vehicles, pure electric vehicles, fuel cell electric vehicles, solar-powered vehicles, and other new energy vehicles. Advantages of NEVs include environmental friendliness and improved ride quality. Disadvantages include difficulty and slow charging times, and low range.

[0003] When existing electric vehicles are in use, the uneven power distribution strategy easily causes power waste in the motor, resulting in insufficient utilization of the motor's dynamic performance and electrical feedback performance, and even the problem of excessive power battery output. At the same time, due to the different road conditions and the different driver types, the motor power cannot be accurately controlled. To this end, we propose a dynamic power distribution control method for the coordinated optimization of the three electric systems of new energy vehicles. Summary of the Invention

[0004] The purpose of the present invention is to solve the problems mentioned in the above background technology, and provide a dynamic power distribution control method for the coordinated optimization of the three electric systems of new energy vehicles.

[0005] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions:

[0006] The dynamic power distribution control method for the coordinated optimization of the three electric systems of new energy vehicles includes:

[0007] An electric motor drive system, which serves as a direct executor of power output;

[0008] A battery management system, which monitors the battery's voltage, current, and temperature in real time, comprehensively assesses the battery's status, and ensures safe and stable operation of the battery;

[0009] An electronic control system, which is responsible for integrating information from the electric motor and battery system and formulating an optimal control strategy;

[0010] A collaborative system, based on the battery management system and the electronic control system, provides safety thresholds and efficiency optimization suggestions to ensure stable operation of the three-electric system.

[0011] Furthermore, the battery management system adjusts the discharge strategy of the battery according to the requirements of the electronic control system, and the battery management system is also responsible for adopting a charging strategy during the battery charging process.

[0012] Furthermore, the battery management system has built-in power electronic control algorithms, including dynamic current regulation algorithm, adaptive voltage control algorithm, sliding mode control algorithm, energy recovery and multi-state management algorithm and intelligent charge and discharge management algorithm.

[0013] Furthermore, the dynamic current regulation algorithm dynamically adjusts the power electronic controller parameters by real-time monitoring of battery current and voltage to achieve optimization of current distribution and power output; the adaptive voltage control algorithm automatically adjusts the output voltage according to the actual voltage and current requirements of the battery management system; the sliding mode control algorithm accurately estimates the battery's state of charge and health status in real time based on a sliding mode observer, and dynamically adjusts the charge and discharge current according to the battery's real-time status based on the sliding mode observer; the energy recovery and multi-state management algorithm converts mechanical energy into electrical energy and feeds it back to the battery during braking or deceleration; the intelligent charge and discharge management algorithm, combined with the battery management system, optimizes the charge and discharge process through intelligent strategies to balance battery life and performance.

[0014] Furthermore, the electronic control system collects vehicle dynamic data in real time based on a sensor unit arranged inside the vehicle and performs rapid processing and analysis of the data.

[0015] Furthermore, the sensor unit includes a vehicle speed sensor, an acceleration sensor, a battery voltage sensor and a current sensor, wherein the vehicle speed sensor is used to collect the vehicle's moving speed in real time, the acceleration sensor is used to collect the vehicle's acceleration in real time, the battery voltage sensor is used to collect the voltage of the vehicle battery in real time, and the current sensor is used to collect the current of the vehicle battery in real time.

[0016] Furthermore, the electronic control system also has a built-in real-time control algorithm, and the electronic control system dynamically adjusts the power output of the electric motor according to the vehicle status and road conditions.

[0017] Further, the following steps are included:

[0018] Step 1: Real-time monitoring: collect vehicle operating status and battery real-time status through sensor units and analyze the data;

[0019] Step 2: Dynamic power distribution: Dynamically adjust the motor output power and perform energy recovery through the real-time control algorithm within the electronic control system;

[0020] Step 3: Generate an allocation strategy based on the result of dynamic power allocation.

[0021] Furthermore, the real-time monitoring includes the following steps:

[0022] Step 11: Data collection and preprocessing: collecting real-time vehicle status information through sensor units;

[0023] Step 12: Data fusion, establishing multi-sensor data association based on the neural network model;

[0024] Step 13: Generating vehicle status information, combining the data after data fusion to form comprehensive vehicle status information, including current vehicle speed, battery power, and load demand.

[0025] Furthermore, the dynamic power allocation includes adjusting the motor power output and optimizing the charging power, wherein the adjusting the motor power output is to dynamically adjust the motor power output according to the vehicle status and road conditions, and the charging power optimization is to achieve grid load prediction and vehicle priority scheduling.

[0026] The beneficial effects of the present invention are as follows:

[0027] 1. The battery management system of the present invention adjusts the battery discharge strategy according to the needs of the electronic control system to provide stable and efficient energy output. The battery management system is also responsible for adopting a charging strategy during the battery charging process to prevent overcharging or over-discharging, thereby extending the battery life.

[0028] 2. The electronic control system of the present invention collects vehicle dynamic data in real time based on the sensor unit installed inside the vehicle and performs rapid data processing and analysis, and dynamically adjusts the motor power output according to the vehicle status and road conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a system working diagram of the present invention.

[0030] Figure 2 It is a system block diagram of the present invention.

[0031] Figure 3 It is a workflow diagram of the present invention.

[0032] Figure 4 It is a workflow diagram of real-time monitoring in the present invention. DETAILED DESCRIPTION

[0033] To make the objectives, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0034] See also Figure 1 - Figure 2The present invention provides a dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles, including:

[0035] Electric motor drive system, the electric motor drive system serves as the direct executor of power output.

[0036] Battery Management System: The battery management system is used to monitor the battery voltage, current, and temperature in real time, conduct a comprehensive assessment of the battery status, and ensure safe and stable operation of the battery.

[0037] The battery management system adjusts the battery's discharge strategy according to the needs of the electronic control system to provide stable and efficient energy output. The battery management system is also responsible for adopting a charging strategy during the battery charging process to prevent overcharging or over-discharging, thereby extending the battery life. The battery management system has built-in power electronic control algorithms, including dynamic current regulation algorithm, adaptive voltage control algorithm, sliding mode control algorithm, energy recovery and polymorphic management algorithm and intelligent charge and discharge management algorithm. The dynamic current regulation algorithm dynamically adjusts the power electronic controller parameters by real-time monitoring of battery current and voltage to achieve optimization of current distribution and power output to adapt to different load requirements. The adaptive voltage control algorithm automatically adjusts the output voltage according to the actual voltage and current requirements of the battery management system to ensure that the system operates in the best working state and improve energy conversion efficiency and driving performance. The sliding mode control algorithm is based on the sliding mode observer to estimate in real time and accurately The battery's state of charge and health status, sliding mode control uses its fast convergence characteristics to effectively handle the uncertainty in the battery's dynamic characteristics, providing reliable data support for battery management. Based on the sliding mode observer, the charging and discharging currents are dynamically adjusted according to the real-time status of the battery to avoid overcharging, over-discharging and overheating. Its robustness ensures that the battery can still maintain safety under complex working conditions. At the same time, it improves energy utilization efficiency by optimizing current distribution, realizes balanced management of each single cell in the battery pack, and ensures the consistency of battery pack performance. Sliding mode control quickly responds to the voltage difference of single cells, suppresses uneven battery aging, and extends the overall life of the system; energy recovery and multi-state management algorithms convert mechanical energy into electrical energy and feed it back to the battery during braking or deceleration, and realizes efficient energy utilization and reduces energy loss through intelligent power management; intelligent charge and discharge management algorithms, combined with the battery management system, optimize the charging and discharging process through intelligent strategies to balance battery life and performance.

[0038] Electronic control system: The electronic control system is responsible for integrating information from the electric motor and battery system and formulating the optimal control strategy.

[0039] The electronic control system collects vehicle dynamic data in real time and processes and analyzes the data quickly based on the sensor units installed inside the vehicle. The sensor units include a vehicle speed sensor, an acceleration sensor, a battery voltage sensor and a current sensor. Among them, the vehicle speed sensor is used to collect the vehicle's moving speed in real time, the acceleration sensor is used to collect the vehicle's acceleration in real time, the battery voltage sensor is used to collect the vehicle's battery voltage in real time, and the current sensor is used to collect the vehicle's battery current in real time. The electronic control system also has a built-in real-time control algorithm. The electronic control system dynamically adjusts the motor power output according to the vehicle status and road conditions.

[0040] The collaborative system is based on the battery management system and the electronic control system to provide safety thresholds and efficiency optimization suggestions to ensure the stable operation of the three-electric system.

[0041] See also Figure 3 - Figure 4 The dynamic power distribution control method for the coordinated optimization of the three electric systems of a new energy vehicle includes the following steps:

[0042] Step 1: Real-time monitoring: collect the vehicle operating status and battery real-time status through the sensor unit and analyze the data; including the following steps:

[0043] Step 11: Data collection and preprocessing: collecting real-time vehicle status information through sensor units.

[0044] Step 12: Data fusion: Establish multi-sensor data association based on the neural network model; solve the problem of low data fault tolerance and improve state estimation accuracy.

[0045] Step 13: Generating vehicle status information, combining the data after data fusion to form comprehensive vehicle status information, including current vehicle speed, battery power, and load demand.

[0046] Step 2: Dynamic power allocation. This involves dynamically adjusting the motor output power and performing energy recovery through a real-time control algorithm within the electronic control system. Dynamic power allocation includes adjusting the motor power output and optimizing the charging power. Adjusting the motor power output involves dynamically adjusting the motor power output based on the vehicle state and road conditions. For example, this involves providing maximum power during sudden acceleration and optimizing the start-stop strategy under congested road conditions. Charging power optimization involves achieving fairness and efficiency in the charging process through grid load forecasting and vehicle priority scheduling, while also reducing grid fluctuations.

[0047] Step 3: Generate an allocation strategy based on the result of dynamic power allocation.

[0048] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A dynamic power distribution control method for coordinated optimization of three electric systems in new energy vehicles, characterized in that: include: An electric motor drive system, which serves as a direct executor of power output; A battery management system, which monitors the battery's voltage, current, and temperature in real time, comprehensively assesses the battery's status, and ensures safe and stable operation of the battery; An electronic control system, which is responsible for integrating information from the electric motor and battery system and formulating an optimal control strategy; A collaborative system, based on the battery management system and the electronic control system, provides safety thresholds and efficiency optimization suggestions to ensure stable operation of the three-electric system.

2. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 1 is characterized in that: The battery management system adjusts the battery discharge strategy according to the requirements of the electronic control system, and is also responsible for adopting a charging strategy during the battery charging process.

3. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 1 is characterized in that: The battery management system has built-in power electronic control algorithms, including dynamic current regulation algorithm, adaptive voltage control algorithm, sliding mode control algorithm, energy recovery and multi-state management algorithm and intelligent charge and discharge management algorithm.

4. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 3 is characterized in that: The dynamic current regulation algorithm monitors the battery current and voltage in real time and dynamically adjusts the power electronic controller parameters to optimize current distribution and power output; An adaptive voltage control algorithm automatically adjusts the output voltage based on the actual voltage and current requirements of the battery management system. A sliding mode control algorithm uses a sliding mode observer to accurately estimate the battery's state of charge and health in real time, and dynamically adjusts the charge and discharge current based on the battery's real-time status. This achieves balanced management of each single cell in the battery pack and ensures consistent battery pack performance. An energy recovery and multi-state management algorithm converts mechanical energy into electrical energy and feeds it back to the battery during braking or deceleration. An intelligent charge and discharge management algorithm, combined with the battery management system, optimizes the charge and discharge process through intelligent strategies to balance battery life and performance.

5. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 1 is characterized in that: The electronic control system collects vehicle dynamic data in real time based on a sensor unit arranged inside the vehicle and performs rapid processing and analysis of the data.

6. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 5 is characterized in that: The sensor unit includes a vehicle speed sensor, an acceleration sensor, a battery voltage sensor and a current sensor, wherein the vehicle speed sensor is used to collect the vehicle's moving speed in real time, the acceleration sensor is used to collect the vehicle's acceleration in real time, the battery voltage sensor is used to collect the voltage of the vehicle battery in real time, and the current sensor is used to collect the current of the vehicle battery in real time.

7. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 1 is characterized in that: The electronic control system also has a built-in real-time control algorithm, which dynamically adjusts the motor power output according to the vehicle status and road conditions.

8. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 1 is characterized in that: The steps include: Step 1: Real-time monitoring: collect vehicle operating status and battery real-time status through sensor units and analyze the data; Step 2: Dynamic power distribution: Dynamically adjust the motor output power and perform energy recovery through the real-time control algorithm within the electronic control system; Step 3: Generate an allocation strategy based on the result of dynamic power allocation.

9. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 8 is characterized in that: The real-time monitoring comprises the following steps: Step 11: Data collection and preprocessing: collecting real-time vehicle status information through sensor units; Step 12: Data fusion, establishing multi-sensor data association based on the neural network model; Step 13: Generating vehicle status information, combining the data after data fusion to form comprehensive vehicle status information, including current vehicle speed, battery power, and load demand.

10. The dynamic power distribution control method for three-electric coordinated optimization of new energy vehicles according to claim 8, characterized in that: The dynamic power allocation includes adjusting the motor power output and optimizing the charging power, wherein the adjustment of the motor power output is to dynamically adjust the motor power output according to the vehicle status and road conditions, and the charging power optimization is to optimize the charging power through grid load forecasting and vehicle priority scheduling.

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