Vehicle-mounted photovoltaic power generation and battery energy collaborative management method

Abstract

The invention provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method, and relates to the technical field of energy collaborative management, and the method comprises the steps: obtaining vehicle-mounted photovoltaic power generation data and battery parameter data, carrying out the data summarization analysis, and setting an energy collaborative management target; on the basis of the environment data and the vehicle-mounted photovoltaic power generation data, obtaining vehicle-mounted photovoltaic power generation prediction data, and obtaining battery energy demand prediction data according to the driving data and the battery parameter data; setting an energy collaborative management strategy based on the energy collaborative management target, performing energy distribution control according to the vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data, and performing energy collaborative management on the vehicle-mounted photovoltaic power generation and the battery; monitoring and evaluating an energy collaborative management process in real time, and optimizing an energy collaborative management strategy and energy distribution control according to an evaluation result; and the energy collaborative management of the vehicle-mounted photovoltaic power generation and the battery is effectively realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy collaborative management, and particularly relates to a vehicle-mounted photovoltaic power generation and battery energy collaborative management method. BACKGROUND

[0002] The endurance performance of the existing pure electric vehicle is mainly limited by the battery performance. The endurance performance can be improved by installing a photovoltaic power generation panel to charge the battery during driving and provide power for vehicle driving. However, the photovoltaic power generation is unstable, and the new energy source will cause energy management difficulties. Energy collaborative management can optimize the energy flow between multiple energy sources and loads, thereby realizing efficient, stable and continuous operation.

[0003] Therefore, the present application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method. SUMMARY

[0004] The present application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method. The vehicle-mounted photovoltaic power generation data and battery parameter data are obtained and analyzed to set an energy collaborative management target. The vehicle-mounted photovoltaic power generation amount prediction data is obtained based on the environmental data and the vehicle-mounted photovoltaic power generation data, and the battery energy demand amount prediction data is obtained based on the driving data and the battery parameter data. The energy collaborative management strategy is set based on the energy collaborative management target, and the energy distribution control is performed based on the vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data. The vehicle-mounted photovoltaic power generation and battery are managed in energy collaboration. The energy collaborative management process is monitored and evaluated in real time, and the energy collaborative management strategy and the energy distribution control are optimized according to the evaluation results. The energy collaborative management of the vehicle-mounted photovoltaic power generation and the battery is effectively realized.

[0005] The present application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method, comprising: Step 1: obtaining vehicle-mounted photovoltaic power generation data and battery parameter data and performing data summary analysis to set an energy collaborative management target; Step 2: obtaining vehicle-mounted photovoltaic power generation amount prediction data based on environmental data and vehicle-mounted photovoltaic power generation data, and obtaining battery energy demand amount prediction data based on driving data and battery parameter data; Step 3: setting an energy collaborative management strategy based on the energy collaborative management target, and performing energy distribution control based on the vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data, and managing the vehicle-mounted photovoltaic power generation and the battery in energy collaboration; Step 4: monitoring and evaluating the energy collaborative management process in real time, and optimizing the energy collaborative management strategy and the energy distribution control according to the evaluation results.

[0006] The application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method, vehicle-mounted photovoltaic power generation data and battery parameter data are acquired and data summary analysis is performed, an energy collaborative management target is set, and the method comprises the following steps: Vehicle-mounted photovoltaic power generation collection parameters are set, monitoring sensors are pre-deployed in a vehicle-mounted photovoltaic panel, and vehicle-mounted photovoltaic power generation data are acquired, wherein the vehicle-mounted photovoltaic power generation data comprise vehicle-mounted photovoltaic power generation amount data, vehicle-mounted photovoltaic panel temperature data and vehicle-mounted photovoltaic panel voltage and current data; Battery parameter data are acquired, wherein the battery parameter data comprise battery voltage parameter data, battery current parameter data, battery temperature parameter data, battery state of charge parameter data and battery state of health parameter data; The vehicle-mounted photovoltaic power generation data and the battery parameter data are subjected to data summary analysis, and an energy collaborative management target is set, wherein the energy collaborative management target comprises a photovoltaic power generation utilization rate target, a battery service life extension target and a photovoltaic power generation and battery energy distribution control target.

[0007] The application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method, vehicle-mounted photovoltaic power generation amount prediction data are acquired based on environmental data and vehicle-mounted photovoltaic power generation data, and battery energy demand amount prediction data are acquired based on driving data and battery parameter data, and the method comprises the following steps: Environmental data are acquired, wherein the environmental data comprise environmental illumination data, environmental temperature data, environmental geographic data and environmental time data; Historical vehicle-mounted photovoltaic power generation data and historical environmental data are acquired, a vehicle-mounted photovoltaic power generation prediction model is constructed, the environmental data and the vehicle-mounted photovoltaic power generation data are input into the vehicle-mounted photovoltaic power generation prediction model, and vehicle-mounted photovoltaic power generation amount prediction data are acquired; Driving data are acquired, wherein the driving data comprise driving route data, driving speed data, driving acceleration data and driving mode data; The battery energy demand amount prediction data are acquired based on the driving data and the battery parameter data.

[0008] The application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method, and the method further comprises the following steps: The vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data are integrated based on prediction time; When it is monitored that the environmental data or the driving data change, the vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data are reacquired and integrated.

[0009] The application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method, which is characterized by the following steps: setting an energy collaborative management strategy based on an energy collaborative management target, and performing energy distribution control on vehicle-mounted photovoltaic power generation and battery energy based on vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data, and performing energy collaborative management on vehicle-mounted photovoltaic power generation and battery energy, comprising the following steps. The energy collaborative management strategy comprises a photovoltaic power generation utilization rate strategy, a battery life extension strategy, and a photovoltaic power generation and battery energy distribution control strategy. The photovoltaic power generation and battery priority is set according to the photovoltaic power generation utilization rate strategy. The battery charge state parameter data charge safety threshold and the battery temperature parameter data temperature safety threshold are set according to the battery life extension strategy. The photovoltaic power generation and battery energy distribution control strategy is dynamically switched according to the vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data, wherein the photovoltaic power generation and battery energy distribution control strategy comprises a photovoltaic power generation energy output control strategy, a battery energy output control strategy, and a hybrid output control strategy. The vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data are quantitatively processed, and when the quantized value of the vehicle-mounted photovoltaic power generation prediction data is not lower than the quantized value of the battery energy demand prediction data, the photovoltaic power generation energy output control strategy is switched to. When the quantized value of the vehicle-mounted photovoltaic power generation prediction data is 0, the battery energy output control strategy is switched to. When the quantized value of the vehicle-mounted photovoltaic power generation prediction data is lower than the quantized value of the battery energy demand prediction data, the hybrid output control strategy is switched to. The vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data are subjected to energy distribution control according to the photovoltaic power generation and battery energy distribution control strategy switched dynamically, and the vehicle-mounted photovoltaic power generation and battery energy are subjected to energy collaborative management. When the dynamically switched photovoltaic power generation and battery energy distribution control strategy is the photovoltaic power generation energy output control strategy, the photovoltaic power generation panel is subjected to energy output distribution control according to the vehicle-mounted photovoltaic power generation prediction data, and the vehicle-mounted photovoltaic power generation prediction data exceeding the battery energy demand prediction data is subjected to energy storage distribution control on the battery. When the dynamically switched photovoltaic power generation and battery energy distribution control strategy is the battery energy output control strategy, the battery is subjected to energy output distribution control according to the battery energy demand prediction data. When the dynamic switching completed photovoltaic power generation and the battery energy distribution control strategy is a hybrid output control strategy, the photovoltaic power generation panel is controlled to output energy and the battery is controlled to output energy according to the priority of the photovoltaic power generation and the battery, the vehicle-mounted photovoltaic power generation amount prediction data, and the battery energy demand amount prediction data. According to the energy distribution control, energy distribution control instructions are generated and delivered to the photovoltaic power generation panel and the battery for energy collaborative management.

[0010] According to the present application, a vehicle-mounted photovoltaic power generation and battery energy collaborative management method is provided, which sets the charge safety threshold of the battery charge state parameter data and the temperature safety threshold of the battery temperature parameter data according to the battery life extension strategy, and further includes: When the battery reaches the upper limit of the charge safety threshold of the battery charge state parameter data, the energy storage distribution control of the battery is stopped; When the battery reaches the lower limit of the charge safety threshold of the battery charge state parameter data, a battery power shortage warning is generated; When the battery reaches the temperature safety threshold of the battery temperature parameter data, the energy distribution control of the battery is limited.

[0011] According to the present application, a vehicle-mounted photovoltaic power generation and battery energy collaborative management method is provided, which monitors and evaluates the energy collaborative management process in real time, optimizes the energy collaborative management strategy and energy distribution control according to the evaluation result, including: The energy collaborative management process is monitored in real time, the energy collaborative management process is evaluated according to the preset evaluation index, and the energy collaborative management evaluation value is obtained, wherein the preset evaluation index includes a photovoltaic power generation utilization rate evaluation index, a battery health state evaluation index, and an energy distribution control balance evaluation index; When the energy collaborative management evaluation value is not lower than the preset evaluation value, it is determined that the energy collaborative management strategy and the energy distribution control do not need to be optimized; When the energy collaborative management evaluation value is lower than the preset evaluation value, the evaluation index abnormal item is located, and the energy collaborative management strategy and the energy distribution control are optimized according to the evaluation index abnormal item.

[0012] According to the present application, a vehicle-mounted photovoltaic power generation and battery energy collaborative management method is provided, which further includes: The current vehicle-mounted photovoltaic power generation amount data and the current battery energy demand amount data are obtained in real time, the photovoltaic power generation amount prediction error value of the current vehicle-mounted photovoltaic power generation amount data and the vehicle-mounted photovoltaic power generation amount prediction data, and the energy demand amount prediction error value of the current battery energy demand amount data and the battery energy demand amount prediction data are determined; According to the photovoltaic power generation amount prediction error value and the energy demand amount prediction error value, the energy feedback distribution control of the energy collaborative management is performed.

[0013] Compared with the prior art, the application has the following beneficial effects: By acquiring the vehicle-mounted photovoltaic power generation data and the battery parameter data and performing data summary analysis, the energy collaborative management target is set; based on the environmental data and the vehicle-mounted photovoltaic power generation data, the vehicle-mounted photovoltaic power generation amount prediction data is acquired, and based on the driving data and the battery parameter data, the battery energy demand amount prediction data is acquired; based on the energy collaborative management target, the energy collaborative management strategy is set, and based on the vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data, the energy distribution control is performed, and the vehicle-mounted photovoltaic power generation and the battery are subjected to energy collaborative management; the energy collaborative management process is monitored and evaluated in real time, and the energy collaborative management strategy and the energy distribution control are optimized according to the evaluation result; the energy collaborative management of the vehicle-mounted photovoltaic power generation and the battery is effectively realized.

[0014] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be achieved and obtained by the structure particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation on the present application. In the drawings: Figure 1 is a flow diagram of a vehicle-mounted photovoltaic power generation and battery energy collaborative management method provided by an embodiment of the present application. DETAILED DESCRIPTION

[0017] The preferred embodiments of the present application will be described below in combination with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and do not limit the present application.

[0018] Example 1: An embodiment of the present application provides a vehicle-mounted photovoltaic power generation and battery energy collaborative management method, as shown in Figure 1 , comprising: Step 1: acquiring vehicle-mounted photovoltaic power generation data and battery parameter data and performing data summary analysis to set an energy collaborative management target; Step 2: based on environmental data and vehicle-mounted photovoltaic power generation data, acquiring vehicle-mounted photovoltaic power generation amount prediction data, and based on driving data and battery parameter data, acquiring battery energy demand amount prediction data; Step 3: setting an energy collaborative management strategy based on the energy collaborative management target, and performing energy distribution control according to the vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data, to perform energy collaborative management on the vehicle-mounted photovoltaic power generation and the battery; Step 4: real-time monitoring and evaluation of the energy collaborative management process, and optimization of the energy collaborative management strategy and the energy distribution control according to the evaluation results.

[0019] In this embodiment, the vehicle-mounted photovoltaic power generation data is obtained by real-time monitoring of the vehicle-mounted photovoltaic panel by pre-deployed monitoring sensors.

[0020] In this embodiment, the battery parameter data refers to relevant data for representing the battery.

[0021] In this embodiment, the energy collaborative management target refers to the target of energy collaborative management on the vehicle-mounted photovoltaic power generation and the battery.

[0022] In this embodiment, the environmental data refers to data of the vehicle driving environment.

[0023] In this embodiment, the vehicle-mounted photovoltaic power generation amount prediction data refers to prediction data about the vehicle-mounted photovoltaic power generation amount obtained according to the environmental data and the vehicle-mounted photovoltaic power generation data.

[0024] In this embodiment, the driving data refers to data in the vehicle driving process.

[0025] In this embodiment, the battery energy demand amount prediction data refers to data of the battery energy demand amount predicted for realizing the driving data.

[0026] In this embodiment, the energy collaborative management strategy refers to a strategy for energy collaborative management on the vehicle-mounted photovoltaic power generation and the battery.

[0027] In this embodiment, the energy distribution control refers to distribution control on the energy output of the vehicle-mounted photovoltaic power generation and the energy output of the battery.

[0028] In this embodiment, the energy collaborative management refers to management on the vehicle-mounted photovoltaic power generation and the battery according to the energy distribution control.

[0029] The working principle and beneficial effects of the above technical solution are: by acquiring vehicle-mounted photovoltaic power generation data and battery parameter data and performing data summary analysis, an energy collaborative management target is set; based on environmental data and vehicle-mounted photovoltaic power generation data, vehicle-mounted photovoltaic power generation capacity prediction data is acquired, and based on driving data and battery parameter data, battery energy demand prediction data is acquired; based on the energy collaborative management target, an energy collaborative management strategy is set, and based on the vehicle-mounted photovoltaic power generation capacity prediction data and the battery energy demand prediction data, energy distribution control is performed, and energy collaborative management is performed on vehicle-mounted photovoltaic power generation and batteries; the energy collaborative management process is monitored and evaluated in real time, and the energy collaborative management strategy and the energy distribution control are optimized according to the evaluation result; the energy collaborative management of vehicle-mounted photovoltaic power generation and batteries is effectively realized.

[0030] Embodiment 2: The embodiment of the application provides a kind of vehicle-mounted photovoltaic power generation and battery energy collaborative management method, obtains vehicle-mounted photovoltaic power generation data and battery parameter data and carries out data summary analysis, set energy collaborative management target, comprising: Set vehicle-mounted photovoltaic power generation collection parameter, pre-deploy monitoring sensor in vehicle-mounted photovoltaic panel, obtain vehicle-mounted photovoltaic power generation data, wherein, vehicle-mounted photovoltaic power generation data includes: vehicle-mounted photovoltaic power generation capacity data, vehicle-mounted photovoltaic panel temperature data and vehicle-mounted photovoltaic panel voltage current data; Obtain battery parameter data, wherein, battery parameter data includes: battery voltage parameter data, battery current parameter data, battery temperature parameter data, battery state of charge parameter data and battery health state parameter data; Vehicle-mounted photovoltaic power generation data and battery parameter data are summarized and analyzed, and energy collaborative management target is set, wherein, energy collaborative management target includes: photovoltaic power generation utilization rate target, battery life extension target and photovoltaic power generation and battery energy distribution control target.

[0031] In this embodiment, vehicle-mounted photovoltaic power generation collection parameter refers to the parameter for data collection of vehicle-mounted photovoltaic panel, such as temperature parameter, voltage parameter and current parameter.

[0032] In this embodiment, vehicle-mounted photovoltaic panel refers to the device for photovoltaic power generation on vehicle.

[0033] In this embodiment, vehicle-mounted photovoltaic power generation data refers to the data acquired by real-time monitoring of vehicle-mounted photovoltaic panel according to pre-deployed monitoring sensor.

[0034] In this embodiment, monitoring sensor refers to the sensor for real-time monitoring of vehicle-mounted photovoltaic panel.

[0035] In this embodiment, the battery parameter data refers to relevant data for representing the battery, such as battery voltage parameter data, battery current parameter data, battery temperature parameter data, battery state of charge parameter data, and battery state of health parameter data.

[0036] In this embodiment, the energy collaborative management target refers to a target for performing energy collaborative management on the vehicle-mounted photovoltaic power generation and the battery, such as a photovoltaic power generation utilization rate being not less than a1.

[0037] The working principle and beneficial effects of the above technical solution are as follows: by obtaining vehicle-mounted photovoltaic power generation data and battery parameter data and performing data summary analysis, an energy collaborative management target is set, thereby laying a data foundation and management target foundation for subsequent energy collaborative management.

[0038] Embodiment 3: The embodiment of the present application provides a kind of vehicle-mounted photovoltaic power generation and the energy collaborative management method of battery, obtains vehicle-mounted photovoltaic power generation amount prediction data based on environmental data and vehicle-mounted photovoltaic power generation data and obtains battery energy demand amount prediction data according to travel data and battery parameter data, comprising: Obtain environmental data, wherein the environmental data includes: environmental illumination data, environmental temperature data, environmental geographic data and environmental time data; Obtain historical vehicle-mounted photovoltaic power generation data and historical environmental data, construct vehicle-mounted photovoltaic power generation prediction model, input environmental data and vehicle-mounted photovoltaic power generation data in vehicle-mounted photovoltaic power generation prediction model, obtain vehicle-mounted photovoltaic power generation amount prediction data; Obtain travel data, wherein the travel data includes: travel route data, travel speed data, travel acceleration data and travel mode data; Obtain battery energy demand amount prediction data based on travel data and battery parameter data.

[0039] In this embodiment, the environmental data refers to data of the vehicle driving environment.

[0040] In this embodiment, the historical vehicle-mounted photovoltaic power generation data refers to vehicle-mounted photovoltaic power generation data in a historical period;The historical environmental data refers to environmental data in a historical period.

[0041] In this embodiment, the vehicle-mounted photovoltaic power generation prediction model refers to a model for predicting vehicle-mounted photovoltaic power generation.

[0042] In this embodiment, the vehicle-mounted photovoltaic power generation amount prediction data refers to prediction data obtained by inputting environmental data and vehicle-mounted photovoltaic power generation data into vehicle-mounted photovoltaic power generation prediction model, such as vehicle-mounted photovoltaic power generation amount prediction data for the next 1 hour.

[0043] In this embodiment, the travel data refers to data in the vehicle driving process.

[0044] In this embodiment, the battery energy demand prediction data refers to data of the battery energy demand obtained by performing prediction on the driving data, for example, the battery energy demand prediction data is not less than b1 for the driving route data.

[0045] The working principle and beneficial effects of the above technical solution are: based on the environmental data and the vehicle-mounted photovoltaic power generation data, the vehicle-mounted photovoltaic power generation prediction data is obtained, and based on the driving data and the battery parameter data, the battery energy demand prediction data is obtained, which is beneficial to subsequent implementation of energy collaborative management of the vehicle-mounted photovoltaic power generation and the battery.

[0046] Embodiment 4: The embodiment of the present application provides a kind of energy collaborative management method of vehicle-mounted photovoltaic power generation and battery, further comprising: Vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data are integrated based on prediction time data; When monitoring that environmental data or driving data changes, vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data are reacquired and integrated.

[0047] In this embodiment, when monitoring that environmental data or driving data changes, vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data are reacquired and integrated, i.e. dynamically adjust vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data, to ensure prediction accuracy.

[0048] The working principle and beneficial effects of the above technical solution are: vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data are integrated based on prediction time data, which is beneficial to subsequent further implementation of energy collaborative management of vehicle-mounted photovoltaic and battery.

[0049] Embodiment 5: The embodiment of the present application provides a kind of energy collaborative management method of vehicle-mounted photovoltaic power generation and battery, based on energy collaborative management target setting energy collaborative management strategy and according to vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data, energy distribution control is carried out, energy collaborative management is carried out to vehicle-mounted photovoltaic power generation and battery, comprising: Based on energy collaborative management target setting energy collaborative management strategy, wherein, energy collaborative management strategy includes: photovoltaic power generation utilization rate strategy, battery life extension strategy and photovoltaic power generation and battery energy distribution control strategy; According to photovoltaic power generation utilization rate strategy, the priority of photovoltaic power generation and battery is set; According to battery life extension strategy, the charge safety threshold of battery state of charge parameter data and the temperature safety threshold of battery temperature parameter data are set; According to the vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data, a photovoltaic power generation and battery energy distribution control strategy is dynamically switched, wherein the photovoltaic power generation and battery energy distribution control strategy comprises a photovoltaic power generation energy output control strategy, a battery energy output control strategy and a hybrid output control strategy. The vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data are quantitatively processed, when the quantized value of the vehicle-mounted photovoltaic power generation prediction data is not lower than the quantized value of the battery energy demand prediction data, the photovoltaic power generation energy output control strategy is switched to. When the quantized value of the vehicle-mounted photovoltaic power generation prediction data is 0, the battery energy output control strategy is switched to. When the quantized value of the vehicle-mounted photovoltaic power generation prediction data is lower than the quantized value of the battery energy demand prediction data, the hybrid output control strategy is switched to. According to the photovoltaic power generation and battery energy distribution control strategy dynamically switched, the vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data are subjected to energy distribution control, and the vehicle-mounted photovoltaic power generation and the battery are subjected to energy collaborative management. When the photovoltaic power generation and battery energy distribution control strategy dynamically switched is the photovoltaic power generation energy output control strategy, the photovoltaic panel is subjected to energy output distribution control according to the vehicle-mounted photovoltaic power generation prediction data, and the battery is subjected to energy storage distribution control according to the vehicle-mounted photovoltaic power generation prediction data exceeding the battery energy demand prediction data. When the photovoltaic power generation and battery energy distribution control strategy dynamically switched is the battery energy output control strategy, the battery is subjected to energy output distribution control according to the battery energy demand prediction data. When the photovoltaic power generation and battery energy distribution control strategy dynamically switched is the hybrid output control strategy, the photovoltaic panel is subjected to energy output distribution control and the battery is subjected to energy output distribution control according to the priority of the photovoltaic power generation and the battery, the vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data. According to the energy distribution control, an energy distribution control instruction is generated and delivered to the photovoltaic panel and the battery for energy collaborative management.

[0050] In this embodiment, the energy collaborative management strategy refers to a strategy for energy collaborative management of the vehicle-mounted photovoltaic power generation and the battery.

[0051] In this embodiment, the photovoltaic power generation utilization rate strategy refers to a strategy for ensuring the utilization rate of photovoltaic power generation when the vehicle-mounted photovoltaic power generation and the battery are subjected to energy collaborative management; the battery life extension strategy refers to a strategy for extending the life of the battery when the vehicle-mounted photovoltaic power generation and the battery are subjected to energy collaborative management; and the photovoltaic power generation and battery energy distribution control strategy refers to a strategy for energy distribution control when the vehicle-mounted photovoltaic power generation and the battery are subjected to energy collaborative management.

[0052] In this embodiment, the priority of photovoltaic power generation and battery is set according to the photovoltaic power generation utilization strategy, for example, photovoltaic power generation is preferentially used for energy output, and the battery is used for energy output later.

[0053] In this embodiment, the charge safety threshold refers to the threshold of the battery state of charge parameter data in a safe state, for example, 0.2-0.8.

[0054] In this embodiment, the temperature safety threshold refers to the threshold of the battery temperature parameter data in a safe state.

[0055] In this embodiment, when the quantized value of the vehicle-mounted photovoltaic power generation prediction data is not lower than the quantized value of the battery energy demand prediction data, that is, the predicted vehicle-mounted photovoltaic power generation exceeds the energy required for vehicle driving.

[0056] In this embodiment, the photovoltaic power generation energy output control strategy refers to the control strategy of photovoltaic power generation alone for energy output.

[0057] In this embodiment, the battery energy output control strategy refers to the control strategy of the battery alone for energy output.

[0058] In this embodiment, the hybrid output control strategy refers to the control strategy of energy output according to photovoltaic power generation and battery.

[0059] In this embodiment, when the quantized value of the vehicle-mounted photovoltaic power generation prediction data is 0, that is, there is no photovoltaic power generation, only energy output control can be performed through the battery.

[0060] In this embodiment, the energy distribution control refers to the control of the vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data according to the photovoltaic power generation and battery energy distribution control strategy completed by dynamic switching, for example, controlling the total energy output c1 of the vehicle-mounted photovoltaic power generation and the battery, wherein the vehicle-mounted photovoltaic power generation energy output c2 and the battery energy output c3.

[0061] In this embodiment, the energy output distribution control of the photovoltaic power generation panel refers to the energy distribution control of the photovoltaic power generation panel (vehicle-mounted photovoltaic panel) according to the vehicle-mounted photovoltaic power generation prediction data, that is, energy output according to vehicle-mounted photovoltaic power generation.

[0062] In this embodiment, the energy storage distribution control of the battery refers to the energy distribution control of the battery according to the vehicle-mounted photovoltaic power generation prediction data exceeding the battery energy demand prediction data, that is, the excess photovoltaic power generation is used for energy storage output of the battery.

[0063] In this embodiment, the energy output distribution control of the battery refers to energy distribution control according to battery energy demand prediction data, that is, energy output of the battery.

[0064] In this embodiment, the energy distribution control instruction refers to an instruction generated according to energy distribution control, for realizing energy collaborative management.

[0065] The working principle and beneficial effects of the above technical solution are: based on the energy collaborative management target, the energy collaborative management strategy is set, and the energy distribution control is performed according to the vehicle-mounted photovoltaic power generation prediction data and the battery energy demand prediction data, thereby effectively realizing the energy collaborative management of the vehicle-mounted photovoltaic power generation and the battery.

[0066] Embodiment 6: The embodiment of the present application provides a kind of energy collaborative management method of vehicle-mounted photovoltaic power generation and battery, according to battery life extension strategy Set the charge safety threshold of battery state of charge parameter data And the temperature safety threshold of battery temperature parameter data, also include: When the battery reaches the upper limit of the charge safety threshold of battery state of charge parameter data, stop energy storage distribution control to the battery; When the battery reaches the lower limit of the charge safety threshold of battery state of charge parameter data, generate battery power shortage warning; When the battery reaches the temperature safety threshold of battery temperature parameter data, limit energy distribution control to the battery.

[0067] In this embodiment, when the battery reaches the upper limit of the charge safety threshold of battery state of charge parameter data, the energy storage distribution control to the battery is stopped, to ensure the battery life.

[0068] In this embodiment, when the battery reaches the lower limit of the charge safety threshold of battery state of charge parameter data, generate battery power shortage warning, to ensure vehicle driving.

[0069] In this embodiment, when the battery reaches the temperature safety threshold of battery temperature parameter data, limit energy distribution control to the battery, that is, control the battery to carry out energy output, and battery temperature parameter data does not exceed temperature safety threshold, for example, reduce the energy output of the battery or stop the energy output of the battery.

[0070] The working principle and beneficial effects of the above technical solution are: according to the battery life extension strategy Set the charge safety threshold of battery state of charge parameter data And the temperature safety threshold of battery temperature parameter data, it is beneficial to ensure the safety of battery.

[0071] Embodiment 7: The embodiment of the present application provides a kind of vehicle-mounted photovoltaic power generation and energy collaborative management method of battery, real-time monitoring and evaluating energy collaborative management process, according to the evaluation result, energy collaborative management strategy and energy distribution control are optimized, comprising: Real-time monitoring energy collaborative management process, according to preset evaluation index, energy collaborative management process is evaluated, and energy collaborative management evaluation value is obtained, wherein, preset evaluation index includes: photovoltaic power generation utilization rate evaluation index, battery health state evaluation index and energy distribution control balance evaluation index; When energy collaborative management evaluation value is not lower than preset evaluation value, it is determined that energy collaborative management strategy and energy distribution control need not be optimized; When energy collaborative management evaluation value is lower than preset evaluation value, locate evaluation index abnormal item, and energy collaborative management strategy and energy distribution control are optimized according to evaluation index abnormal item.

[0072] In the embodiment, preset evaluation index refers to the index for evaluating energy collaborative management process.

[0073] In the embodiment, energy collaborative management evaluation value refers to the quantitative value obtained by evaluating energy collaborative management process according to preset evaluation index.

[0074] In the embodiment, preset evaluation value refers to the quantitative value for judging whether energy collaborative management strategy and energy distribution control need to be optimized.

[0075] In the embodiment, evaluation index abnormal item refers to the index item that causes energy collaborative management evaluation value to be lower than preset evaluation value, for example, photovoltaic power generation utilization rate is low, and then energy collaborative management evaluation value is lower than preset evaluation value, so photovoltaic power generation utilization rate is evaluation index abnormal item.

[0076] The working principle and beneficial effects of the above technical solution are: real-time monitoring and evaluating energy collaborative management process, according to the evaluation result, energy collaborative management strategy and energy distribution control are optimized, and further ensure that energy collaborative management of vehicle-mounted photovoltaic power generation and battery is ensured.

[0077] Embodiment 8: The embodiment of the present application provides a kind of vehicle-mounted photovoltaic power generation and energy collaborative management method of battery, further comprising: Real-time acquisition current vehicle-mounted photovoltaic power generation capacity data and current battery energy demand data, determine current vehicle-mounted photovoltaic power generation capacity data and photovoltaic power generation capacity prediction error value of vehicle-mounted photovoltaic power generation capacity prediction data and energy demand data and energy demand prediction error value of energy demand prediction data of battery energy demand; According to photovoltaic power generation capacity prediction error value and energy demand prediction error value, energy feedback distribution control is carried out on energy collaborative management.

[0078] In this embodiment, the current vehicle-mounted photovoltaic power generation data refers to the real-time vehicle-mounted photovoltaic power generation data obtained in the current period; and the current battery energy demand data refers to the battery energy demand data in the current period.

[0079] In this embodiment, the photovoltaic power generation prediction error value refers to the error value between the current vehicle-mounted photovoltaic power generation data and the vehicle-mounted photovoltaic power generation prediction data.

[0080] In this embodiment, the energy demand prediction error value refers to the error value between the current battery energy demand data and the battery energy demand prediction data.

[0081] In this embodiment, the energy feedback distribution control refers to the control of the energy collaborative management according to the photovoltaic power generation prediction error value and the energy demand prediction error value, for example, controlling the vehicle-mounted photovoltaic power generation and the total battery energy output c1 to be unchanged, wherein the vehicle-mounted photovoltaic power generation energy output c2 is feedback-distributed to c4, and the battery energy output c3 is feedback-distributed to c5.

[0082] The working principle and beneficial effects of the above technical solution are: by performing the energy feedback distribution control on the energy collaborative management according to the photovoltaic power generation prediction error value and the energy demand prediction error value, the energy collaborative management of the vehicle-mounted photovoltaic power generation and the battery is ensured.

[0083] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for energy cooperative management of photovoltaic power generation and battery on vehicle, characterized in that, Comprise: Step 1: Obtain vehicle-mounted photovoltaic power generation data and battery parameter data and perform data summary analysis, set energy collaborative management target; Step 2: Obtain vehicle-mounted photovoltaic power generation prediction data based on environmental data and vehicle-mounted photovoltaic power generation data, and obtain battery energy demand prediction data based on driving data and battery parameter data; Step 3: Set energy collaborative management strategy based on energy collaborative management target, and perform energy distribution control based on vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data, and perform energy collaborative management on vehicle-mounted photovoltaic power generation and battery; Step 4: Real-time monitoring and evaluation of energy collaborative management process, and optimization of energy collaborative management strategy and energy distribution control according to evaluation results.

2. The energy collaborative management method of vehicle-mounted photovoltaic power generation and battery according to claim 1, characterized in that, Obtain vehicle-mounted photovoltaic power generation data and battery parameter data and perform data summary analysis, set energy collaborative management target, comprising: Set vehicle-mounted photovoltaic power generation collection parameters, pre-deploy monitoring sensors in vehicle-mounted photovoltaic panels, and obtain vehicle-mounted photovoltaic power generation data, wherein the vehicle-mounted photovoltaic power generation data includes vehicle-mounted photovoltaic power generation data, vehicle-mounted photovoltaic panel temperature data, and vehicle-mounted photovoltaic panel voltage and current data; Obtain battery parameter data, wherein the battery parameter data includes battery voltage parameter data, battery current parameter data, battery temperature parameter data, battery state of charge parameter data, and battery health state parameter data; Perform data summary analysis on vehicle-mounted photovoltaic power generation data and battery parameter data, and set energy collaborative management target, wherein the energy collaborative management target includes photovoltaic power generation utilization rate target, battery life extension target, and photovoltaic power generation and battery energy distribution control target.

3. The energy collaborative management method of vehicle-mounted photovoltaic power generation and battery according to claim 1, characterized in that, Obtain vehicle-mounted photovoltaic power generation prediction data based on environmental data and vehicle-mounted photovoltaic power generation data, and obtain battery energy demand prediction data based on driving data and battery parameter data, comprising: Obtain environmental data, wherein the environmental data includes environmental light data, environmental temperature data, environmental geographic data, and environmental time data; Obtain historical vehicle-mounted photovoltaic power generation data and historical environmental data, construct a vehicle-mounted photovoltaic power generation prediction model, input environmental data and vehicle-mounted photovoltaic power generation data into the vehicle-mounted photovoltaic power generation prediction model, and obtain vehicle-mounted photovoltaic power generation prediction data; Obtain driving data, wherein the driving data includes driving route data, driving speed data, driving acceleration data, and driving mode data; Obtain battery energy demand prediction data based on driving data and battery parameter data.

4. The energy collaborative management method of vehicle-mounted photovoltaic power generation and battery according to claim 3, characterized in that, Also include: Integrate vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data based on prediction time; When changes in environmental data or driving data are monitored, re-obtain vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data and perform data integration.

5. The energy collaborative management method of vehicle-mounted photovoltaic power generation and battery according to claim 1, characterized in that, Set energy collaborative management strategy based on energy collaborative management target, and perform energy distribution control based on vehicle-mounted photovoltaic power generation prediction data and battery energy demand prediction data, and perform energy collaborative management on vehicle-mounted photovoltaic power generation and battery, comprising: The energy collaborative management strategy is set based on the energy collaborative management target, wherein the energy collaborative management strategy comprises a photovoltaic power generation utilization rate strategy, a battery life extension strategy, and a photovoltaic power generation and battery energy distribution control strategy; The priority of the photovoltaic power generation and the battery is set according to the photovoltaic power generation utilization rate strategy; The charge safety threshold of the battery state of charge parameter data and the temperature safety threshold of the battery temperature parameter data are set according to the battery life extension strategy; The photovoltaic power generation and battery energy distribution control strategy is dynamically switched according to the vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data, wherein the photovoltaic power generation and battery energy distribution control strategy comprises a photovoltaic power generation energy output control strategy, a battery energy output control strategy, and a hybrid output control strategy; The vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data are quantitatively processed, when the quantization value of the vehicle-mounted photovoltaic power generation amount prediction data is not lower than the quantization value of the battery energy demand amount prediction data, the photovoltaic power generation energy output control strategy is switched to; When the quantization value of the vehicle-mounted photovoltaic power generation amount prediction data is 0, the battery energy output control strategy is switched to; When the quantization value of the vehicle-mounted photovoltaic power generation amount prediction data is lower than the quantization value of the battery energy demand amount prediction data, the hybrid output control strategy is switched to; The vehicle-mounted photovoltaic power generation amount prediction data and the battery energy demand amount prediction data are controlled by energy distribution according to the photovoltaic power generation and battery energy distribution control strategy after dynamic switching, and the vehicle-mounted photovoltaic power generation and battery are collaboratively managed by energy; When the photovoltaic power generation and battery energy distribution control strategy after dynamic switching is the photovoltaic power generation energy output control strategy, the photovoltaic power generation panel is controlled by energy output distribution according to the vehicle-mounted photovoltaic power generation amount prediction data, and the vehicle-mounted photovoltaic power generation amount prediction data exceeding the battery energy demand amount prediction data is controlled by energy storage distribution to the battery; When the photovoltaic power generation and battery energy distribution control strategy after dynamic switching is the battery energy output control strategy, the battery is controlled by energy output distribution according to the battery energy demand amount prediction data; When the photovoltaic power generation and battery energy distribution control strategy after dynamic switching is the hybrid output control strategy, the photovoltaic power generation panel is controlled by energy output distribution and the battery is controlled by energy output distribution according to the priority of the photovoltaic power generation and the battery, the vehicle-mounted photovoltaic power generation amount prediction data, and the battery energy demand amount prediction data; The energy distribution control instruction is generated according to the energy distribution control and is delivered to the photovoltaic power generation panel and the battery for energy collaborative management.

6. The energy cooperative management method of claim 5, wherein, The charge safety threshold of the battery state of charge parameter data and the temperature safety threshold of the battery temperature parameter data are set according to the battery life extension strategy, and the method further comprises: When the battery reaches the upper limit of the charge safety threshold of the battery state of charge parameter data, the energy storage distribution control to the battery is stopped; When the battery reaches the lower limit of the charge safety threshold of the battery state of charge parameter data, a battery power shortage warning is generated; When the battery reaches the temperature safety threshold of the battery temperature parameter data, the energy distribution control to the battery is limited.

7. The energy cooperative management method of photovoltaic power generation and battery for vehicle according to claim 1, characterized in that, Real-time monitoring and evaluation of energy collaborative management process, optimizing energy collaborative management strategy and energy distribution control according to the evaluation results, including: Real-time monitoring of energy collaborative management process, evaluating the energy collaborative management process according to the preset evaluation index, and obtaining the energy collaborative management evaluation value, wherein the preset evaluation index includes: photovoltaic power generation utilization rate evaluation index, battery health state evaluation index and energy distribution control balance evaluation index; When the energy collaborative management evaluation value is not lower than the preset evaluation value, it is determined that the energy collaborative management strategy and the energy distribution control do not need to be optimized; When the energy collaborative management evaluation value is lower than the preset evaluation value, the evaluation index abnormal item is located, and the energy collaborative management strategy and the energy distribution control are optimized according to the evaluation index abnormal item.

8. The energy cooperative management method of photovoltaic power generation and battery for vehicle according to claim 1, characterized in that, Also includes: Real-time acquisition of current vehicle-mounted photovoltaic power generation data and current battery energy demand data, determination of photovoltaic power generation prediction error value of current vehicle-mounted photovoltaic power generation data and vehicle-mounted photovoltaic power generation prediction data, and energy demand prediction error value of current battery energy demand data and battery energy demand prediction data; According to the photovoltaic power generation prediction error value and the energy demand prediction error value, the energy feedback distribution control of the energy collaborative management is carried out.

Images