WO2019184848A1

WO2019184848A1 - Electric vehicle and prompt system therefor

Info

Publication number: WO2019184848A1
Application number: PCT/CN2019/079453
Authority: WO
Inventors: 杨子华; 邓林旺; 吕纯; 冯天宇; 林思岐
Original assignee: 比亚迪股份有限公司
Priority date: 2018-03-30
Filing date: 2019-03-25
Publication date: 2019-10-03
Also published as: CN110324394A

Abstract

Provided are an electric vehicle and a prompt system therefor. The prompt system comprises a cloud server, a client, and a battery management system (BMS) disposed on an electric vehicle, wherein the BMS is used to collect a state parameter of a power battery of the electric vehicle, generate first-level data according to the state parameter of the power battery, and send the first-level data to the cloud server; and the cloud server is used to determine, according to the first-level data, whether a prompt condition is met, and if the prompt condition is met, send prompt information to the client bound to the electric vehicle, thereby enabling a user to know, in a timely manner, the current operating state of the power battery in the electric vehicle so as to facilitate the processing of a problematic power battery or a cell therein.

Description

Electric vehicle and its prompting system

Cross-reference to related applications

The present application is based on a Chinese patent application No. 201100 297 926 926, filed on Jan. 30, 2011, the entire disclosure of which is hereby incorporated by reference.

Technical field

The present application relates to the field of electric vehicle technology, and in particular, to a reminder system for an electric vehicle, a method for prompting an electric vehicle, and an electric vehicle.

Background technique

Lithium-ion battery has been widely used in electric vehicles and other fields due to its high energy density, high output voltage, good cycle performance, low self-discharge rate, fast charge and discharge, and high charging efficiency. .

Different from traditional fuel vehicles, the starting system is the focus of maintenance. The maintenance of electric vehicles is focused on motors, gearboxes and power batteries. As a power source, the maintenance, maintenance and repair of power lithium-ion batteries is very important.

At present, the maintenance mode of the electric vehicle power lithium-ion battery is that the owner regularly monitors and diagnoses the battery at the service store. When a certain degree of attenuation of a single cell or a few cells is found to be high, it will be based on the after-sales maintenance manual. A few cells with a higher degree of attenuation are replaced, and the replaced lithium-ion battery is subjected to a charge and discharge cycle to confirm the battery consistency, and then the BMS (Battery Management System) equalization function is combined. To maximize the remaining available capacity of the battery.

However, the above maintenance method is too passive and lacks predictability. Once the capacity of one or several cells in the battery decays faster than other cells, the owner can only feel the driving range of the electric car is not accurate or attenuated, but not Know the specific fault information of the battery, and there is no information to suggest that the vehicle needs to be repaired. Once the owner is inspected, it will lead to the cracking of the faulty unit, which may cause serious economic losses to the user and the user may use it. Poor experience.

At the same time, the above maintenance method is to obtain the UQ charging curve of each monomer by performing a charge and discharge cycle test on the battery, and judge and calculate the remaining available capacity of the monomer and the SOC misalignment according to the consistency of the single curve, thereby identifying the faulty monomer. The number of the section, and the replacement of the single battery or the entire battery as the case may be, the maintenance method is cumbersome and time consuming.

Summary of the invention

The present application aims to solve at least one of the technical problems in the above-mentioned techniques to some extent. To this end, the first object of the present application is to propose a prompting system for an electric vehicle, so that the user can timely understand the current operating state of the power battery in the electric vehicle, so as to facilitate processing of the problematic power battery or its individual. .

A second object of the present application is to propose a prompting method for an electric vehicle.

A third object of the present application is to provide an electric vehicle.

A fourth object of the present application is to propose a cloud server.

The first aspect of the present application provides a prompting system for an electric vehicle, comprising a cloud server, a client, and a battery management system BMS disposed on the electric vehicle, wherein the BMS is configured to collect the electric a state parameter of the power battery of the automobile, and generating first-level data according to the state parameter of the power battery, and transmitting the first-level data to the cloud server; the cloud server, configured to determine, according to the first-level data Whether the prompt condition is reached, and if the above prompt condition is reached, the prompt message is sent to the client bound to the electric vehicle.

According to the prompting system of the electric vehicle according to the embodiment of the present application, the state parameter of the power battery of the electric vehicle is collected by the BMS, and the first level data is generated according to the state parameter of the power battery, and the first level data is sent to the cloud server, and then passes through the cloud server. Determining whether the prompt condition is reached according to the first-level data reported by the BMS, and sending a prompt message to the client bound to the electric vehicle when the above-mentioned prompt condition is reached, thereby enabling the user to know the current running state of the power battery in the electric vehicle in time. In order to facilitate the treatment of the problematic power battery or its monomer.

The embodiment of the second aspect of the present application provides a method for prompting an electric vehicle, wherein the electric vehicle is provided with a battery management system BMS, wherein the BMS collects state parameters of the power battery of the electric vehicle, and according to the Generating the first level data of the state parameter of the power battery, and sending the first level data to the cloud server; the cloud server determines whether the prompt condition is reached according to the first level data, and if the prompt condition is reached, The car-bound client sends a prompt message.

According to the prompting method of the electric vehicle according to the embodiment of the present application, the state parameter of the power battery of the electric vehicle is first collected by the BMS, and the first level data is generated according to the state parameter of the power battery, and the first level data is sent to the cloud server, and then the cloud is The server determines whether the prompt condition is met according to the primary data reported by the BMS, and sends a prompt message to the client bound to the electric vehicle when the above prompt condition is reached, thereby enabling the user to know the current operation of the power battery in the electric vehicle in time. State to facilitate handling of the problematic power battery or its individual.

An embodiment of the third aspect of the present application provides an electric vehicle including: a power battery, the power battery includes a plurality of single cells; a battery management system BMS, the BMS includes: a plurality of battery collectors BIC, the plurality of Corresponding to a plurality of single cells in the power battery, respectively, for collecting state parameters of the plurality of single cells, the battery control unit BCU, the BCU is connected to the plurality of BICs, and The cloud server performs communication, and the BCU is configured to generate the first-level data according to a state parameter of the power battery, and send the first-level data to the cloud server, so that the cloud server is in a judgment center. When the primary data reaches the prompt condition, the prompt information is sent to the client bound to the electric vehicle.

In an embodiment of the present application, the BCU is further configured to: receive secondary data fed back by the cloud server, and update a reference curve pre-stored in the BMS according to the secondary data; The cloud server further acquires the vehicle identification code VIN of the electric vehicle and the primary data, and generates the secondary data according to the VIN and the primary data, and sends the secondary data to the BMS.

In an embodiment of the present application, the BCU includes: a first controller, configured to perform vehicle control according to a state parameter of the power battery; and a second controller, configured to communicate with the cloud server, and Generating the primary data according to the state parameter of the power battery, and receiving secondary data of the cloud server, and updating a reference curve pre-stored in the BMS according to the secondary data.

In an embodiment of the present application, the secondary data includes a charge and discharge voltage U-current I reference curve of the power battery, an open circuit voltage OCV-battery capacity Q reference curve, a battery capacity Q-health state SOH reference curve, One or more of the resistance R-health state SOH-current I-temperature T reference curve and the historical self-discharge rate reference curve.

In an embodiment of the present application, the primary data includes at least a rest time of the power battery, a temperature of the power battery, a state of charge of the power battery, and a state of the power battery. One of them.

According to the electric vehicle of the embodiment of the present application, the state parameter of the power battery of the electric vehicle is collected by the BMS, and the first level data is generated according to the state parameter of the power battery, and the first level data is sent to the cloud server for reporting according to the BMS through the cloud server. The first level data determines whether the prompt condition is reached, and sends a prompt message to the client bound to the electric vehicle when the above prompt condition is reached, thereby enabling the user to know the current running state of the power battery in the electric vehicle in time, so as to facilitate The problematic power battery or its monomer is processed.

The embodiment of the fourth aspect of the present application provides a cloud server, comprising: a determining module, configured to determine, according to the primary data reported by the BMS of the electric vehicle, whether the prompt condition is reached, wherein the BMS is based on the status parameter of the power battery Generating the first level data; the first sending module is configured to send the prompt information to the client bound to the electric vehicle when the prompt condition is reached.

In an embodiment of the present application, the cloud server further includes: an obtaining module, configured to acquire a vehicle identification code VIN and the first level data of the electric vehicle; and a generating module, configured to use the VIN and the Generating the secondary data according to the primary data; the second sending module is configured to send the secondary data to the BMS, so that the BMS compares the reference curve pre-stored in the BMS according to the secondary data. Update.

In an embodiment of the present application, the first level data includes a rest time of the power battery, and when the rest time is greater than a first preset time threshold, the cloud server sends the solution to the client. Tips for charging and balancing maintenance; and/or

The first level data includes a temperature of the power battery, and when the temperature of the power battery is greater than a first preset temperature threshold or less than a second preset temperature threshold, the cloud server sends a temperature abnormality to the client. The prompt, wherein the second preset temperature threshold is less than the first preset temperature threshold; and/or the primary data includes a state of charge of the power battery, when a state of charge of the power battery When the load is full or overloaded, and the maintenance time is greater than the second preset time threshold, the cloud server sends a prompt to the client; and/or the primary data includes the SOH of the power battery, when When the SOH of the power battery is less than a preset threshold, the cloud server sends a prompt to the client.

According to the cloud server of the embodiment of the present application, the determining module determines whether the prompt condition is reached according to the first-level data reported by the BMS of the electric vehicle, and the first sending module reaches the customer bound to the electric vehicle when the prompt condition is reached. The terminal sends an alarm message, thereby enabling the user to know the current operating state of the power battery in the electric vehicle in time to facilitate processing of the problematic power battery or its individual.

DRAWINGS

1 is a structural block diagram of a system for prompting according to a user's usage habits of an electric vehicle according to an embodiment of the present application;

2 is a structural block diagram of a system for prompting according to a user's usage habits of an electric vehicle according to an embodiment of the present application;

3 is a structural block diagram of a system for prompting according to a user's usage habits of an electric vehicle according to another embodiment of the present application;

4 is a flow chart of a method for prompting according to a user's usage habits of an electric vehicle according to an embodiment of the present application;

FIG. 5 is a structural block diagram of an electric vehicle according to an embodiment of the present application; FIG.

6 is a structural block diagram of a cloud server according to an embodiment of the present application;

FIG. 7 is a structural block diagram of a cloud server according to another embodiment of the present application.

detailed description

The embodiments of the present application are described in detail below, and the examples of the embodiments are illustrated in the drawings, wherein the same or similar reference numerals are used to refer to the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are intended to be illustrative, and are not to be construed as limiting.

A cloud server, an electric vehicle, and a prompting system and method thereof according to embodiments of the present application are described below with reference to the accompanying drawings.

1 is a block diagram showing the structure of a prompting system of an electric vehicle according to an embodiment of the present application. As shown in FIG. 1, the system 100 includes a cloud server 10, a client 30, and a battery management system BMS 20 disposed above the electric vehicle.

The BMS 20 is configured to collect state parameters of the power battery of the electric vehicle, generate first level data according to the state parameters of the power battery, and send the first level data to the cloud server 10.

In the embodiment of the present application, the state parameters of the power battery include, but are not limited to, voltage, current, temperature, power, balanced power, charge and discharge capacity, mileage, charge and discharge times, charge and discharge time, etc. during charging and discharging of the power battery. .

The BMS 20 can upload the primary data to the cloud server 10 through wireless communication methods such as OBD (On-Board Diagnostic), in-vehicle wireless network, WiFi, Bluetooth, cellular network, etc., every preset time.

The cloud server 10 is configured to determine whether the prompt condition is reached based on the primary data, and if the prompt condition is reached, send an alarm message to the client 30 bound to the electric vehicle.

The prompt condition may be at least but not limited to, the rest time of the power battery is greater than the first preset time threshold; the temperature of the power battery is greater than the first preset temperature threshold, or is less than the second preset temperature threshold; The state is full load or overload, and the maintenance time is greater than the second preset time threshold; the SOH of the power battery is less than one of the preset thresholds.

It can be understood that, when the cloud server 10 determines that the prompt condition is met according to the primary data, it can be powered by GPS (Global Positioning System) and/or GSM (Global System for Mobile Communication). The car-bound client 30 sends a prompt message to remind the user to actively maintain the power battery of the electric vehicle. The client 30 may be a mobile terminal of a user set by an independent electric vehicle, such as a smart phone, a Pad, etc., or may be installed or integrated on an electric vehicle, such as a car multimedia.

In the first example of the present application, the primary data includes a rest time of the power battery, and when the rest time is greater than the first preset time threshold, the cloud server 10 sends a prompt to the client 30 to perform charging and equalization maintenance.

Wherein, when it is detected that the power battery has not updated the charging and discharging data for a long time, that is, the power battery is left for a long time, at this time, the power battery may cause a decrease in the remaining available capacity of the power battery due to self-discharge and capacity attenuation, and even a certain occurrence. The degree of SOC (State of Charge) is misaligned. When the timeout period of the power battery is greater than the first preset time, the cloud server 10 determines that the prompt condition is reached, and sends an alarm prompt (such as the first prompt tone or the corresponding voice prompt) to the client, such as the owner's mobile phone, by way of wireless communication. , text message prompts, etc., to remind the owner to charge and balance the maintenance of the electric car.

In the second example of the present application, the first level data includes the temperature of the power battery, and when the temperature of the power battery is greater than the first preset temperature threshold or less than the second preset temperature threshold, the cloud server 10 sends the temperature to the client 30. The prompt of the abnormal temperature, wherein the second preset temperature threshold is less than the first preset temperature threshold.

When it is detected that the operating temperature of the power battery is at a high temperature for a long time, for example, when the temperature of the power battery is greater than the first preset temperature threshold, the cloud server 10 determines that the prompt condition is reached, and sends the battery temperature to the client, such as the owner's mobile phone, by wireless communication. Abnormal alarm prompts (such as the second prompt tone, or corresponding voice prompts, text message prompts, etc.), to remind the owner to go to the service store as soon as possible to repair the power battery overheating reasons (such as temperature sampling and monitoring functions are abnormal, battery cooling system is abnormal, etc. ).

When it is detected that the operating temperature of the power battery is at a low temperature for a long time, for example, when the temperature of the power battery is less than the second preset temperature threshold, the cloud server 10 determines that the prompt condition is reached, and sends the battery temperature to the client, such as the owner's mobile phone, by means of wireless communication. Abnormal alarm prompts (such as the third prompt tone, or corresponding voice prompts, text message prompts, etc.), to remind the owner to go to the service store as soon as possible to check the power battery temperature is too low (such as temperature sampling and monitoring function is abnormal, battery cooling system is whether Abnormal, etc.).

In the third example of the present application, the primary data includes a state of charge of the power battery, and when the state of charge of the power battery is full load or overload, and the maintenance time is greater than a second preset time threshold, the cloud server 10 A prompt is sent to the client 30.

When it is detected that the power battery discharge phase is at full load or overload for a long time, that is, the output power is close to the maximum SOP (State of Power) value, the cloud server 10 determines that the prompt condition is reached. And wirelessly communicate to the client, such as the owner's mobile phone, to send a battery temperature overload alarm prompt (such as the fourth prompt tone, or corresponding voice prompts, text message prompts, etc.) to remind the owner to drive the vehicle gently.

In the fourth example of the present application, the primary data includes an SOH (State of Health) of the power battery, and when the SOH of the power battery is less than a preset threshold, the cloud server 10 sends a prompt to the client 30.

When it is detected that the SOH of the power battery is lower than the replacement threshold specified by the manufacturer, that is, less than the preset threshold, the cloud server 10 determines that the prompt condition is reached, and sends a battery temperature abnormality alarm prompt to the client, such as the owner's mobile phone, by means of wireless communication. (such as the fifth prompt tone, or corresponding voice prompts, text message prompts, etc.), to remind the owner to go to the service store to replace the power battery as soon as possible.

In an embodiment of the present application, the cloud server 10 is further configured to acquire the vehicle identification code VIN and the primary data of the electric vehicle, generate secondary data according to the VIN and the primary data, and send the secondary data to the BMS 20.

The secondary data includes a charging and discharging UI (ie, voltage-current) reference curve of the power battery, an OCV-Q (ie, open circuit voltage-battery capacity) reference curve, a Q-SOH (ie, battery capacity-constant state) reference curve, R-SOH-IT (ie, resistance-health state-current-temperature) reference curve and historical self-discharge rate reference curve.

The cloud server 10 may be provided with a plurality of historical databases, each of which corresponds to a different electric vehicle, and may be distinguished by the vehicle identification code VIN of the electric vehicle. The vehicle identification code VIN may include a frame number, a power battery number, a production batch number, and the like.

The BMS 20 sends the first-level data to the cloud server 10, and also sends the vehicle identification code VIN, and the cloud server 10 searches for the corresponding historical data according to the VIN, and generates secondary data according to the historical data and the received primary data, and The secondary data is sent to the BMS 20.

The BMS 20 receives the secondary data fed back by the cloud server 10 and updates the reference curve pre-stored in the BMS 20 based on the secondary data.

Thus, with the deepening of the power battery charging and discharging cycle, the BMS 20 continuously fits the new first-level data and uploads it to the cloud server 10. The cloud server 10 continuously generates new secondary data based on the historical data and the primary data, and transmits back to the cloud data. BMS10, continuous loop iteration, can make the prediction result of the whole battery system closer to the real state of the power battery, and is beneficial to the effective management of the power battery.

Among them, the historical data may include a historical charge and discharge U-I curve of the power battery, a historical OCV-Q curve, a historical Q-SOH curve, a historical R-SOH-I-T curve, and a historical self-discharge rate.

In the embodiment of the present application, as shown in FIG. 2, the BMS 20 includes a plurality of battery collectors BIC 21 and a battery control unit BCU 22.

Wherein, the plurality of BICs 21 respectively correspond to a plurality of single cells in the power battery, and are used for collecting state parameters of the plurality of single cells. The BCU 22 is connected to the plurality of BICs 21 and communicates with the cloud server 10. The BCU 22 is configured to generate primary data according to the state parameters of the power battery, and receive the secondary data of the cloud server 10, and the reference stored in the BMS 20 according to the secondary data. The curve is updated.

Each BIC21 can send primary data to the BCU 22 via CAN (Controller Area Network), in-vehicle network FlexRay or Daisy Chain (daisy chain).

In this embodiment, the BCU 22 and all of the BICs 21 can be assembled with all of the battery cells pack inside the cabin of an electric vehicle.

BIC21 is used for battery cell voltage sampling and monitoring, battery equalization, battery pack temperature sampling and monitoring, BCU22 for bus current detection, system insulation monitoring, battery system up/down management, battery system thermal management, battery state of charge SOC (State of Charge) estimation, battery health state SOH (State of Health) estimation, battery power state SOP (State of Power) estimation, fault diagnosis, vehicle communication and online program update, data recording.

As shown in FIG. 3, the BCU 22 includes a first controller 22a and a second controller 22b. The first controller 22a is configured to perform vehicle control according to the state parameter of the power battery. The second controller 22b is configured to communicate with the cloud server 10, generate primary data according to the state parameters of the power battery, receive secondary data of the cloud server, and update the reference curve pre-stored in the BMS according to the secondary data.

In this embodiment, the BCU 22 has a powerful data storage space and a high-speed data processing speed dual MCU (ie, the first controller 22a and the second controller 22b), has off-line data processing capability, and can be accessed through a wireless communication module. The wireless communication method performs data interaction with the cloud server 10. Further, the cloud server 10 performs cloud computing and big data analysis on the battery state information and the state parameters of the entire life cycle of the power battery to realize current state management and future state prediction of the power battery.

In summary, according to the prompting system of the electric vehicle according to the embodiment of the present application, the interaction technology between the cloud server and the BMS and the client, and the machine learning technology can continuously track the entire life cycle of the electric vehicle power battery from the factory to the replacement. Data, so that you can fully grasp the historical dynamic data of the battery, more predictable and more accurate information monitoring and fault diagnosis of the battery; through the wireless network transmission, the prompt information such as predictive maintenance and maintenance suggestions are pushed from the cloud server to the customer. At the end, the owner is reminded to maintain and maintain the battery, which improves the humanization and intelligence of the after-sales service, thereby enhancing the user experience. In addition, the service store can directly use the intelligent analysis results of the cloud server to conduct targeted maintenance and repair of the power battery in a targeted manner, thereby saving battery charging and discharging cycle detection and diagnosis time, improving the service efficiency of the service store, and saving The user's time, thereby improving economic efficiency and social efficiency.

4 is a flow chart of a prompting method of an electric vehicle according to an embodiment of the present application.

In an embodiment of the present application, a battery management system BMS is disposed above the electric vehicle.

As shown in FIG. 4, the prompting method includes the following steps:

S101: The BMS collects the state parameter of the power battery of the electric vehicle, generates first level data according to the state parameter of the power battery, and sends the first level data to the cloud server.

S102: The cloud server determines, according to the primary data, whether the prompt condition is reached, and if the prompt condition is met, sending the prompt information to the client bound to the electric vehicle.

In an embodiment of the present application, the cloud server further acquires the vehicle identification code VIN and the primary data of the electric vehicle, generates secondary data according to the VIN and the primary data, and sends the secondary data to the BMS; the BMS receives the cloud server. The secondary data is fed back and the reference curve pre-stored in the BMS is updated based on the secondary data.

The secondary data includes a charge and discharge U-I reference curve of the power battery, an OCV-Q reference curve, a Q-SOH reference curve, an R-SOH-I-T reference curve, and a historical self-discharge rate reference curve.

In the first example of the present application, the first level data includes a rest time of the power battery, and when the rest time is greater than the first preset time threshold, the cloud server sends a prompt for charging and equalizing maintenance to the client.

In the second example of the present application, the first level data includes the temperature of the power battery, and when the temperature of the power battery is greater than the first preset temperature threshold or less than the second preset temperature threshold, the cloud server sends the temperature abnormality to the client. The prompt, wherein the second preset temperature threshold is less than the first preset temperature threshold.

In the third example of the present application, the primary data includes a state of charge of the power battery, and when the state of charge of the power battery is full load or overload, and the maintenance time is greater than a second preset time threshold, the cloud server The client sends a prompt.

In the fourth example of the present application, the primary data includes the SOH of the power battery, and when the SOH of the power battery is less than a preset threshold, the cloud server sends a prompt to the client.

It should be noted that other specific embodiments of the method for prompting the electric vehicle according to the embodiment of the present application can refer to the specific embodiment of the prompting system for the electric vehicle of the above embodiment.

According to the prompting system of the electric vehicle according to the embodiment of the present application, the interaction technology between the cloud server and the BMS and the client, and the machine learning technology can continuously track the data of the entire life cycle of the electric vehicle power battery from the factory to the replacement, thereby It can fully grasp the historical dynamic data of the battery, and is more predictable and more accurate for battery information monitoring and fault diagnosis. Through the wireless network transmission, the prompt information such as predictive maintenance and maintenance suggestions will be pushed from the cloud server to the client, reminding The owner maintains and maintains the battery, which improves the user-friendliness and intelligence of the after-sales service, thereby enhancing the user experience. In addition, the service store can directly use the intelligent analysis results of the cloud server to conduct targeted maintenance and repair of the power battery in a targeted manner, thereby saving battery charging and discharging cycle detection and diagnosis time, improving the service efficiency of the service store, and saving The user's time, thereby improving economic efficiency and social efficiency.

FIG. 5 is a structural block diagram of an electric vehicle according to an embodiment of the present application. As shown in FIG. 5, the electric vehicle 1000 includes a power battery 200 and a BMS 20.

Among them, the power battery 200 includes a plurality of single cells.

Referring to FIG. 2, the BMS 20 includes a plurality of battery collectors BIC 21 and a battery control unit BCU 22.

Wherein, the plurality of BICs 21 respectively correspond to the plurality of single cells, and are used for collecting state parameters of the plurality of single cells. The BCU 22 is connected to the plurality of BICs 21 and communicates with the cloud server 10. The BCU 22 is configured to generate primary data according to the state parameters of the power battery, and send the primary data to the cloud server 10, so that the cloud server determines that the primary data is reached. A prompt message is sent to the client bound to the electric vehicle when the condition is prompted.

In an embodiment of the present application, the primary data includes at least one of a resting time of the power battery, a temperature of the power battery, a state of charge of the power battery, and a SOH of the power battery.

When the rest time is greater than the first preset time threshold, the cloud server sends a prompt for charging and equalizing maintenance to the client; when the temperature of the power battery is greater than the first preset temperature threshold or less than the second preset temperature threshold, The cloud server sends a prompt for the temperature abnormality to the client, where the second preset temperature threshold is less than the first preset temperature threshold; when the power state of the power battery is full load or overload, and the maintenance time is greater than the second preset time At the threshold, the cloud server sends a prompt to the client; when the SOH of the power battery is less than a preset threshold, the cloud server sends a prompt to the client.

In one embodiment of the present application, the cloud server also acquires the vehicle identification code VIN and the primary data of the electric vehicle 1000, and generates secondary data based on the VIN and the primary data, and transmits the secondary data to the BMS 20.

The BCU 22 is further configured to receive secondary data fed back by the cloud server, and update the reference curve pre-stored in the BMS 20 according to the secondary data.

Referring to FIG. 3, the BCU 22 includes a first controller 22a and a second controller 22b. The first controller 22a is configured to perform vehicle control according to the state parameter of the power battery. The second controller 22b is configured to communicate with the cloud server 10, generate primary data according to the state parameters of the power battery, receive secondary data of the cloud server, and update the reference curve pre-stored in the BMS according to the secondary data.

In one embodiment of the present application, the secondary data includes a charge and discharge U-I reference curve, an OCV-Q reference curve, a Q-SOH reference curve, an R-SOH-I-T reference curve, and a historical self-discharge rate reference curve for the power battery.

It should be noted that, in other specific embodiments of the electric vehicle according to the embodiment of the present application, reference may be made to the specific embodiment of the BMS 20 in the prompting system of the electric vehicle of the above embodiment.

The electric vehicle of the embodiment of the present application communicates with the cloud server through the BMS to perform longitudinal analysis on the relevant parameters of the power battery of the electric vehicle through the cloud server, so that the user can timely understand the state information of the power battery, so as to actively perform the power battery. maintenance.

FIG. 6 is a structural block diagram of a cloud server according to an embodiment of the present application. As shown in FIG. 6, the cloud server 10 includes a judging module 11 and a first sending module 12.

The determining module 11 is configured to determine whether the prompt condition is reached according to the primary data reported by the BMS of the electric vehicle, wherein the BMS generates the primary data according to the status parameter of the power battery.

The first sending module 12 is configured to send the prompt information to the client bound to the electric vehicle when the prompt condition is reached.

The primary data may include, but is not limited to, the resting time of the power battery, the temperature of the power battery, the state of charge of the power battery, and the SOH of the power battery. When the rest time is greater than the first preset time threshold, the first sending module 12 sends a prompt for charging and equalizing maintenance to the client; when the temperature of the power battery is greater than the first preset temperature threshold, or is less than the second pre- When the temperature threshold is set, the first sending module 12 sends a prompt for the temperature abnormality to the client, where the second preset temperature threshold is less than the first preset temperature threshold; when the state of charge of the power battery is full load or overload, and When the maintenance time is greater than the second preset time threshold, the first sending module 12 sends a prompt to the client; when the SOH of the power battery is less than the preset threshold, the first sending module 12 sends a prompt to the client.

In an embodiment of the present application, as shown in FIG. 7, the cloud server 10 further includes an obtaining module 13, a generating module 14, and a second sending module 15.

The obtaining module 13 is configured to acquire the vehicle identification code VIN and the primary data of the electric vehicle. The generating module 14 is configured to generate secondary data based on the VIN and the primary data. The second sending module 15 is configured to send the secondary data to the BMS, so that the BMS updates the reference curve pre-stored in the BMS according to the secondary data.

Optionally, the secondary data includes a charge and discharge U-I reference curve of the power battery, an OCV-Q reference curve, a Q-SOH reference curve, an R-SOH-I-T reference curve, and a historical self-discharge rate reference curve.

It should be noted that, in other specific implementation manners of the cloud server 10 of the embodiment of the present application, reference may be made to the specific implementation manner of the cloud server 10 in the prompting system of the electric vehicle of the above embodiment.

The cloud server of the embodiment of the present application can continuously track the data of the entire life cycle of the electric vehicle power battery from the factory to the replacement by interacting with the BMS and the client, and according to the machine learning technology, thereby comprehensively grasping the historical dynamic data of the battery. It is more predictable and more accurate for information monitoring and fault diagnosis of the battery; it can also push the prompt information such as predictive maintenance and maintenance suggestions to the client by the cloud server to remind the owner to maintain and maintain the battery, and improve the after-sales service. The humanization and intelligence of the service will enhance the user experience. In addition, the service store can directly use the intelligent analysis results of the cloud server to conduct targeted maintenance and repair of the power battery in a targeted manner, thereby saving battery charging and discharging cycle detection and diagnosis time, improving the service efficiency of the service store, and saving The user's time, thereby improving economic efficiency and social efficiency.

In the description of the present application, it is to be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", " Rear, Left, Right, Vertical, Horizontal, Top, Bottom, Inner, Out, Clockwise, Counterclockwise, Axial The orientation or positional relationship of the "radial", "circumferential" and the like is based on the orientation or positional relationship shown in the drawings, and is merely for the convenience of describing the present application and the simplified description, and does not indicate or imply the indicated device or The elements must have a particular orientation, are constructed and operated in a particular orientation, and are therefore not to be construed as limiting.

Moreover, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include one or more of the features either explicitly or implicitly. In the description of the present application, the meaning of "a plurality" is two or more unless specifically and specifically defined otherwise.

In the present application, the terms "installation", "connected", "connected", "fixed" and the like shall be understood broadly, and may be either a fixed connection or a detachable connection, unless otherwise explicitly stated and defined. , or integrated; can be mechanical connection, or can be electrical connection; can be directly connected, or can be indirectly connected through an intermediate medium, can be the internal communication of two elements or the interaction of two elements. For those skilled in the art, the specific meanings of the above terms in the present application can be understood on a case-by-case basis.

In the present application, the first feature "on" or "below" the second feature may be the direct contact of the first and second features, or the first and second features are indirectly through the intermediate medium, unless otherwise explicitly stated and defined. contact. Moreover, the first feature "above", "above" and "above" the second feature may be that the first feature is directly above or above the second feature, or merely that the first feature level is higher than the second feature. The first feature "below", "below" and "below" the second feature may be that the first feature is directly below or obliquely below the second feature, or merely that the first feature level is less than the second feature.

In the description of the present specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means a specific feature described in connection with the embodiment or example. A structure, material or feature is included in at least one embodiment or example of the application. In the present specification, the schematic representation of the above terms is not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, various embodiments or examples described in the specification, as well as features of various embodiments or examples, may be combined and combined.

While the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are illustrative and are not to be construed as limiting the scope of the present application. The embodiments are subject to variations, modifications, substitutions and variations.

Claims

A reminder system for an electric vehicle, comprising: a cloud server, a client, and a battery management system BMS disposed on the electric vehicle, wherein

The BMS is configured to collect a state parameter of a power battery of the electric vehicle, generate first level data according to the state parameter of the power battery, and send the first level data to the cloud server;

The cloud server is configured to determine, according to the first-level data, whether a prompt condition is reached, and if the prompt condition is reached, send a prompt message to a client that is bound to the electric vehicle.
The prompting system for an electric vehicle according to claim 1, wherein

The BMS is further configured to receive secondary data fed back by the cloud server, and update a reference curve pre-stored in the BMS according to the secondary data;

The cloud server is further configured to acquire a vehicle identification code VIN and the primary data of the electric vehicle, and generate the secondary data according to the VIN and the primary data, and the secondary data Sent to the BMS.
The prompting system for an electric vehicle according to claim 1 or 2, wherein the BMS comprises:

a plurality of battery collectors BIC, the plurality of BICs respectively corresponding to the plurality of single cells in the power battery, for collecting state parameters of the plurality of single cells;

a battery control unit BCU, wherein the BCU is connected to the plurality of BICs and is in communication with the cloud server, the BCU is configured to generate the first level data according to a state parameter of the power battery, and receive the cloud Secondary data of the server, and updating the reference curve pre-stored in the BMS according to the secondary data.
The prompting system for an electric vehicle according to any one of claims 1 to 3, wherein the BCU comprises:

a first controller, configured to perform vehicle control according to a state parameter of the power battery;

a second controller, configured to communicate with the cloud server, generate the primary data according to a status parameter of the power battery, and receive secondary data of the cloud server, and according to the secondary data pair The reference curve pre-stored in the BMS is updated.
The prompting system for an electric vehicle according to claim 2, wherein said secondary data comprises a charge and discharge voltage U-current I reference curve of said power battery, an open circuit voltage OCV-battery capacity Q reference curve, and a battery capacity. One or more of the Q-health state SOH reference curve, the resistance R-health state SOH-current I-temperature T reference curve, and the historical self-discharge rate reference curve.
The prompting system for an electric vehicle according to any one of claims 1 to 5, wherein the primary data includes a resting time of the power battery, when the resting time is greater than a first preset time At the threshold, the cloud server sends a prompt to the client to perform charging and equalization maintenance.
The prompting system for an electric vehicle according to any one of claims 1 to 6, wherein the primary data includes a temperature of the power battery, and when a temperature of the power battery is greater than a first preset temperature threshold The cloud server sends a prompt for the temperature abnormality to the client, where the second preset temperature threshold is smaller than the first preset temperature threshold.
The prompting system for an electric vehicle according to any one of claims 1 to 7, wherein the primary data includes a state of charge of the power battery, and when the state of charge of the power battery is full When the load is overloaded and the maintenance time is greater than the second preset time threshold, the cloud server sends a prompt to the client.
The prompting system for an electric vehicle according to any one of claims 1 to 8, wherein the primary data includes an SOH of the power battery, and when an SOH of the power battery is less than a preset threshold, The cloud server sends a prompt to the client.
A method for prompting an electric vehicle, characterized in that a battery management system BMS is disposed on the electric vehicle, wherein

The BMS collects a state parameter of a power battery of the electric vehicle, and generates first level data according to the state parameter of the power battery, and sends the first level data to a cloud server;

The cloud server determines, according to the first-level data, whether the prompt condition is reached, and if the prompt condition is reached, sending the prompt information to the client bound to the electric vehicle.
The method for prompting an electric vehicle according to claim 10, further comprising:

The cloud server acquires the vehicle identification code VIN and the primary data of the electric vehicle, and generates the secondary data according to the VIN and the primary data, and sends the secondary data to the BMS;

The BMS receives the secondary data fed back by the cloud server, and updates the reference curve pre-stored in the BMS according to the secondary data.
The method for prompting an electric vehicle according to claim 10 or 11, wherein the secondary data includes a charging/discharging voltage U-current I reference curve of the power battery, an open circuit voltage OCV-battery capacity Q reference curve, Battery capacity Q-health state SOH reference curve, resistance R-health state SOH-current I-temperature T reference curve and historical self-discharge rate reference curve one or more.
The method for prompting an electric vehicle according to any one of claims 10 to 12, wherein the primary data includes a rest time of the power battery, when the rest time is greater than a first preset time At the threshold, the cloud server sends a prompt to the client to perform charging and equalization maintenance.
The method for prompting an electric vehicle according to any one of claims 10 to 13, wherein the primary data includes a temperature of the power battery, and when a temperature of the power battery is greater than a first preset temperature threshold The cloud server sends a prompt for the temperature abnormality to the client, where the second preset temperature threshold is smaller than the first preset temperature threshold.
The method for prompting an electric vehicle according to any one of claims 10 to 14, wherein the primary data includes a state of charge of the power battery, and when the state of charge of the power battery is full When the load is overloaded and the maintenance time is greater than the second preset time threshold, the cloud server sends a prompt to the client.
The method for prompting an electric vehicle according to any one of claims 10 to 15, wherein the primary data includes an SOH of the power battery, and when the SOH of the power battery is less than a preset threshold, The cloud server sends a prompt to the client.
An electric vehicle characterized by comprising:

a power battery, the power battery comprising a plurality of single cells;

A battery management system BMS, the BMS comprising:

a plurality of battery collectors BIC respectively corresponding to the plurality of single cells in the power battery for collecting state parameters of the plurality of single cells,

a battery control unit BCU, the BCU is connected to the plurality of BICs, and is in communication with the cloud server, the BCU is configured to generate the first level data according to a state parameter of the power battery, and the first The level data is sent to the cloud server, so that the cloud server sends the prompt information to the client bound to the electric vehicle when determining that the primary data reaches the prompt condition.