阅读说明：本技术 一种智能电池热管理方法 (Intelligent battery thermal management method ) 是由 龚春忠 张永 李鹏 李佩佩 于 2021-08-23 设计创作，主要内容包括：本发明为一种智能电池热管理方法,包括：获取电池温度及车辆状态信息；当电池当前温度低于电池回充温度时,由回收的能量为车身电器供电,电池不进行回充；当电池当前温度低于电池最佳状态温度时,根据车辆状态信息预测本次行驶里程,若预测本次行驶里程小于第一设定值,则采用非电池能量给电池加热；当电池当前温度低于电池最佳状态温度时,将驱动系统运行产生的热量传输给电池。本发明的优点是：在电池限制回充时,避免动能浪费,减少电池能量输出；根据预测里程选择采用非电池能量给电池加热还是电池能量给电池加热,避免在短距离行驶时产生电池能量的浪费；利用驱动系统运行产生的热量给电池加热,能够提高电池升温效率。(The invention relates to an intelligent battery heat management method, which comprises the following steps: acquiring battery temperature and vehicle state information; when the current temperature of the battery is lower than the battery recharging temperature, the recovered energy supplies power to the electric appliance of the vehicle body, and the battery is not recharged; when the current temperature of the battery is lower than the optimal state temperature of the battery, predicting the driving mileage according to the vehicle state information, and if the predicted driving mileage is smaller than a first set value, heating the battery by adopting non-battery energy; and when the current temperature of the battery is lower than the optimal state temperature of the battery, transmitting heat generated by the operation of the driving system to the battery. The invention has the advantages that: when the battery is limited to be recharged, kinetic energy waste is avoided, and the energy output of the battery is reduced; according to the predicted mileage, selecting whether non-battery energy or battery energy is adopted to heat the battery, so as to avoid waste of the battery energy during short-distance driving; the battery is heated by heat generated by the operation of the driving system, so that the temperature rise efficiency of the battery can be improved.)

1. An intelligent battery thermal management method is characterized in that: the method comprises the following steps:

acquiring battery temperature and vehicle state information;

when the current temperature of the battery is lower than the battery recharging temperature, the kinetic energy recovery function is started, the recovered energy is used for supplying power to the electric appliance of the vehicle body, and the battery is not recharged;

when the current temperature of the battery is lower than the optimal state temperature of the battery, predicting the driving mileage according to the vehicle state information, and if the predicted driving mileage is smaller than a first set value, heating the battery by using non-battery energy;

when the current temperature of the battery is lower than the optimal state temperature of the battery, the heat generated by the operation of the driving system is transmitted to the battery through the heat circulating system to heat the battery.

2. The intelligent battery thermal management method according to claim 1, wherein: when the current temperature of the battery is higher than the recharging temperature of the battery, the battery is recharged by the recovered energy in a kinetic energy recovery state, and the battery supplies power for the electric appliance of the vehicle body.

3. The intelligent battery thermal management method according to claim 1, wherein: and when the current temperature of the battery is lower than the optimal state temperature of the battery, if the driving mileage is predicted to be more than or equal to a first set value, heating the battery by adopting non-battery energy and battery energy at the same time.

4. The intelligent battery thermal management method according to claim 1 or 3, wherein: the non-battery energy includes energy generated during kinetic energy recovery of the vehicle and heat generated during operation of the drive system.

5. The intelligent battery thermal management method according to claim 1 or 3, wherein: the method for predicting the driving mileage comprises the following steps:

s101: acquiring vehicle state information, wherein the vehicle state information comprises vehicle speed, vehicle acceleration, vehicle position information and time information;

s102: predicting the average acceleration of the vehicle in a future period of time through a convolutional neural network model based on the vehicle state information;

s103: acquiring a future vehicle speed, a future vehicle acceleration, a future vehicle position, future time information and a driving mileage in a future period of time according to the average acceleration of the vehicle in the future period of time;

s104: inputting the future vehicle speed, the future vehicle acceleration, the future vehicle position and the future time information into a convolutional neural network model, and predicting the average acceleration of the vehicle in a future period of time;

s105: repeating the steps S103-S104 until the future vehicle speed and the vehicle acceleration are predicted to be 0 for a plurality of times;

s106: and accumulating the traveled mileage within a future period of time obtained by executing step S103 each time to obtain a traveled mileage prediction result.

6. The intelligent battery thermal management method according to claim 5, wherein: the convolutional neural network model is obtained by training vehicle owner historical driving data.

7. The intelligent battery thermal management method according to claim 5, wherein: the first set value is determined by:

s201: acquiring power p1 of a driving system at different battery temperatures and different vehicle speeds;

s202: acquiring a heat generation coefficient a of the driving system, and transmitting heat generated by the operation of the driving system to a transmission coefficient b of a battery and the average power p2 of a battery heater by the circulating system;

s203: acquiring the current battery temperature, and calculating the heat Q required for heating the battery to the optimal state temperature of the battery;

s204: predicting the average acceleration of the vehicle in the future by adopting a convolutional neural network model to obtain the vehicle speed at each time in the futureSimultaneously calculating the temperature of the battery at each moment according to the time and the vehicle speed at each future momentWherein the content of the first and second substances,which represents the temperature of the battery at the time t,represents the battery temperature at time t-1,which represents the specific heat capacity of the battery,represents the power of the drive system at time t-1,is the time difference between the time t and the time t-1;

s205: according to the formula

The time T required for the battery to warm up to the battery optimum state temperature is calculated,representing the power of the drive system at time t, i.e. the battery temperatureThe speed of the vehicle isPower of the time drive system;

s206: calculating the distance traveled by the vehicle during the time T, i.e. the first set value。

8. The intelligent battery thermal management method according to claim 1, wherein: when the current temperature of the battery is higher than the optimal state temperature of the battery, the heat radiator radiates heat to the driving system.

Technical Field

The invention relates to the field of electric automobiles, in particular to an intelligent battery thermal management method.

Background

Currently, the problem of the electric automobile's cold fearing ' is still one of the key problems affecting the consumer's acceptance of the product. For this reason, a heat preservation technique for batteries, a heat pump technique, and the like are gradually applied to electric vehicles.

The existing battery low-temperature protection and temperature rise scheme mainly aims at limiting battery recharging when the battery is at low temperature and directly heating the battery through a battery heater when the battery is at low temperature. Although the scheme can effectively relieve the problem of cold resistance of the battery, certain defects still exist, on one hand, when the battery is limited to be recharged, the kinetic energy recovery function of the vehicle is closed, so that energy cannot be recovered, and on the other hand, when the battery is directly heated by using a battery heater during short-distance running, the battery does not reach the optimal state temperature of the battery, and a user easily reaches a destination. Under the condition, the heat energy generated by the battery heater can be dissipated along with the standing of the vehicle, certain energy waste exists, and the endurance mileage of the electric automobile can be influenced.

Disclosure of Invention

The invention mainly solves the problems and provides the intelligent battery heat management method which has high energy utilization rate in a low-temperature environment and can improve the driving range of the electric automobile.

The invention solves the technical problem by adopting the technical scheme that an intelligent battery heat management method comprises the following steps:

acquiring battery temperature and vehicle state information;

when the current temperature of the battery is lower than the battery recharging temperature, the kinetic energy recovery function is started, the recovered energy is used for supplying power to the electric appliance of the vehicle body, and the battery is not recharged;

when the current temperature of the battery is lower than the optimal state temperature of the battery, predicting the driving mileage according to the vehicle state information, and if the predicted driving mileage is smaller than a first set value, heating the battery by using non-battery energy;

when the current temperature of the battery is lower than the optimal state temperature of the battery, the heat generated by the operation of the driving system is transmitted to the battery through the heat circulating system to heat the battery.

As a preferable scheme of the above scheme, when the current temperature of the battery is higher than the battery recharging temperature, in the kinetic energy recovery state, the recovered capacity recharges the battery, and the battery supplies power to the vehicle body electrical appliance.

As a preferable scheme of the above scheme, when the current temperature of the battery is lower than the optimal state temperature of the battery, if it is predicted that the driving mileage is greater than or equal to the first set value, the non-battery energy and the electric energy are simultaneously used for heating the battery.

As a preferable mode of the above, the non-battery energy includes energy generated when the vehicle performs kinetic energy recovery and heat generated by operation of a driving system.

As a preferable mode of the above mode, the predicting the current mileage includes:

s101: acquiring vehicle state information, wherein the vehicle state information comprises vehicle speed, vehicle acceleration, vehicle position information and time information;

s102: predicting the average acceleration of the vehicle in a future period of time through a convolutional neural network model based on the vehicle state information;

s103: acquiring vehicle state information in a future period of time, namely a future vehicle speed, a future vehicle acceleration, a future vehicle position, future time information and a driving range in the future period of time according to the vehicle average acceleration in the future period of time;

s104: inputting the future vehicle speed, the future vehicle acceleration, the future vehicle position and the future time information into a convolutional neural network model, and predicting the average acceleration of the vehicle in a future period of time;

s105: repeating the steps S103-S104 until the future vehicle speed and the vehicle acceleration are predicted to be 0 for a plurality of times;

s106: and accumulating the traveled mileage within a future period of time obtained by executing step S103 each time to obtain a traveled mileage prediction result.

As a preferable scheme of the scheme, the convolutional neural network model is obtained by training vehicle owner historical driving data.

As a preferable mode of the above, the first set value is determined by:

s201: acquiring power p1 of a driving system at different battery temperatures and different vehicle speeds;

s202: acquiring a heat generation coefficient a of the driving system, and transmitting heat generated by the operation of the driving system to a transmission coefficient b of the battery and the average power p2 of the battery heater by the heat circulating system;

s203: acquiring the current battery temperature, and calculating the heat Q required for heating the battery to the optimal state temperature of the battery;

s204: predicting the average acceleration of the vehicle in the future by adopting a convolutional neural network model to obtain the vehicle speed at each time in the futureSimultaneously calculating the temperature of the battery at each moment according to the time and the vehicle speed at each future moment

Wherein the content of the first and second substances,which represents the temperature of the battery at the time t,represents the temperature of the battery at time t-1, C represents the specific heat capacity of the battery,represents the power of the drive system at time t-1,is the time difference between the time t and the time t-1;

s205: according to the formula

The time T required for the battery to warm up to the battery optimum state temperature is calculated,representing the power of the drive system at time t, i.e. the battery temperatureThe speed of the vehicle isPower of the time drive system;

s206: the travel distance of the vehicle within the time T, i.e., the first set value, is calculated.

As a preferable mode of the above, when the current temperature of the battery is higher than the optimum state temperature of the battery, the heat sink dissipates the heat of the driving system.

The invention has the advantages that: when the battery is limited to be recharged, the energy generated by kinetic energy recovery is utilized to supply power to the electric appliances of the vehicle body, so that the kinetic energy waste is avoided, and the energy output of the battery is reduced; the driving mileage can be predicted, and non-battery energy or battery energy is selected to heat the battery according to the predicted mileage, so that waste of the battery energy during short-distance driving is avoided; the battery is heated by heat generated by the operation of the driving system, so that the temperature rise efficiency of the battery can be improved.

Drawings

Fig. 1 is a flowchart illustrating a method for predicting the current driving mileage in the embodiment.

Fig. 2 is a flowchart illustrating a first setting value determining method according to an embodiment.

Detailed Description

The technical solution of the present invention is further described below by way of examples with reference to the accompanying drawings.

Example (b):

the intelligent battery thermal management method in the embodiment comprises the following steps:

s1: acquiring battery temperature and vehicle state information;

s2: determining a battery thermal management strategy according to the battery temperature, specifically, when the current temperature of the battery is lower than the battery recharging temperature, starting a kinetic energy recovery function, supplying power to a vehicle body electrical appliance by the recovered energy, wherein the battery is not recharged, and the vehicle body battery comprises a battery heater; when the current temperature of the battery is higher than the recharging temperature of the battery, the battery is recharged by the recovered energy in a kinetic energy recovery state, and the battery supplies power for the electric appliance of the vehicle body. When the current temperature of the battery is lower than the optimal state temperature of the battery, predicting the driving mileage according to the vehicle state information, and if the predicted driving mileage is smaller than a first set value, heating the battery by using non-battery energy; and when the current temperature of the battery is lower than the optimal state temperature of the battery, if the driving mileage is predicted to be more than or equal to a first set value, heating the battery by adopting non-battery energy and electric energy at the same time. When the current temperature of the battery is lower than the optimal state temperature of the battery, transmitting heat generated by the operation of the driving system to the battery through a heat circulating system to heat the battery; when the current temperature of the battery is higher than the optimal state temperature of the battery, the heat radiator radiates heat to the driving system.

In this embodiment, the non-battery energy includes energy generated when the vehicle recovers kinetic energy and heat generated by operation of the driving system, and one of the main expression forms of heating the battery by the non-battery energy is to supply power to the battery heater by using the energy generated by the kinetic energy recovery, so that the battery heater heats the battery; the other main expression form is that the heat generated by the operation of the driving system is transmitted to the battery through a heat circulating system, the heat circulating system is a water circulating system, a radiator is further arranged on the heat circulating system, and the radiator can transmit the energy in the heat circulating system to the air.

In this embodiment, as shown in fig. 1, the method for predicting the driving mileage includes the following steps:

s101: acquiring vehicle state information, wherein the vehicle state information comprises vehicle speed, vehicle acceleration, vehicle position information and time information;

s102: predicting the average acceleration of the vehicle in a period of time in the future through a convolutional neural network model based on the vehicle state information, wherein the convolutional neural network model is obtained by training historical driving data of a vehicle owner, and in addition, the convolutional neural network is secondarily trained according to the driving data when the vehicle is used every time;

s103: acquiring a future vehicle speed, a future vehicle acceleration, a future vehicle position, future time information and a driving mileage in a future period of time according to the average vehicle acceleration in the future period of time;

s104: inputting the future vehicle speed, the future vehicle acceleration, the future vehicle position and the future time information into a convolutional neural network model, and predicting the average acceleration of the vehicle in a future period of time;

s105: repeating the steps S103-S104 until the future vehicle speed and the vehicle acceleration are predicted to be 0 for a plurality of times;

s106: and accumulating the traveled mileage within a future period of time obtained by executing step S103 each time to obtain a traveled mileage prediction result.

In the method for predicting the mileage traveled this time according to the embodiment, the traveled this time is divided into a plurality of time slots, each time slot is assumed to be 5 seconds, the current time is assumed to be 0 second, the current vehicle state information is used for predicting the vehicle average acceleration of 5 seconds in the future, the vehicle state information of the 5 th second in the future and the traveled mileage of the vehicle within the 5 seconds can be calculated according to the predicted vehicle average acceleration of 5 seconds in the future, the vehicle state information of the 10 th second in the future is acquired by using the vehicle state information of the 5 th second in the future, the vehicle state information of the 15 th second in the future is acquired by using the vehicle state information of the 10 th second in the future until the vehicle speed and the acceleration within a plurality of consecutive time slots are predicted to be 0, that is, the vehicle is considered to be stopped, the traveled this time is finished, and finally, the traveled mileage of the vehicle in each time slot is acquired by accumulating the traveled mileage.

In this embodiment, the determining the first setting value by the following method, as shown in fig. 2, includes:

s201: acquiring power p1 of a driving system at different battery temperatures and different vehicle speeds, wherein the data is obtained through vehicle use data of a user;

s202: acquiring a heat generation coefficient a of the driving system, and transmitting heat generated by the operation of the driving system to a transmission coefficient b of a battery and the average power p2 of a battery heater by the circulating system;

s203: acquiring the current battery temperature, and calculating the heat Q required for heating the battery to the optimal state temperature of the battery;

s204: predicting the average acceleration of the vehicle in the future by adopting a convolutional neural network model to obtain the vehicle speed at each time in the futureSimultaneously calculating the temperature of the battery at each moment according to the time and the vehicle speed at each future moment

Wherein the content of the first and second substances,which represents the temperature of the battery at the time t,represents the temperature of the battery at time t-1, C represents the specific heat capacity of the battery,represents the power of the drive system at time t-1,is the time difference between the time t and the time t-1;

s205: according to the formula

The time T required for the battery to warm up to the battery optimum state temperature is calculated,representing the power of the drive system at time t, i.e. the battery temperatureThe speed of the vehicle isPower of the time drive system;

s206: the travel distance of the vehicle within the time T, i.e., the first set value, is calculated.

The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.