A new energy vehicle battery management system that matches alarm schemes according to battery status

Abstract

The present invention relates to the technical field of data acquisition and processing, and specifically to a new energy vehicle battery management system that matches an alarm scheme according to the battery status. The battery management system includes a battery detection unit, an analysis and processing unit, and a monitoring and alarm unit. The analysis and processing unit analyzes the battery status based on information from the battery pack, grades the battery status, formulates different alarm schemes, and establishes a system model and an observation model to predict the battery status trend based on the linear relationship between the battery status level and the battery status trend. The prediction result is then integrated and analyzed with the temperature inside the vehicle to obtain a risk coefficient, which is sent to the user and emergency contacts. At the same time, a high-decibel sound and light alarm is activated, effectively improving the emergency response speed, reducing the losses caused by fire, and realizing personalized alarm notifications, ensuring that relevant parties are informed of dangerous situations in a timely manner and take action.

Description

Technical Field

[0001] The present invention relates to the technical field of data acquisition and processing, and in particular to a new energy vehicle battery management system that matches an alarm scheme according to battery status. Background Art

[0002] The battery management system is an important technology that can collect voltage, current, temperature and other data of new energy vehicle battery packs in real time, helping the system to monitor battery status in real time, control the battery in a timely manner and trigger the corresponding alarm mechanism. By analyzing and processing the collected data, the system can better understand the working status, trends and laws of the battery, and provide support for the system's intelligent decision-making. The battery status setting of traditional systems is usually a fixed value, which has poor adaptability to different battery types and different usage scenarios. The same voltage or temperature can have different meanings in different situations. Traditional systems find it difficult to accurately predict the battery health status and issue different levels of alarms based on different battery status. To solve this problem, we provide a new energy vehicle battery management system that matches the alarm scheme according to the battery status. Summary of the Invention

[0003] The purpose of the present invention is to provide a new energy vehicle battery management system that matches an alarm scheme according to the battery status, so as to solve the problems raised in the above background technology.

[0004] To achieve the above objectives, a new energy vehicle battery management system is provided that matches an alarm scheme according to the battery status, including a battery detection unit, an analysis and processing unit, and a monitoring and alarm unit;

[0005] The battery detection unit is used to detect the voltage, current and temperature information of the battery pack in real time through the installed sensors, and send this information to the analysis and processing unit;

[0006] The analysis and processing unit is used to receive information from the battery pack, analyze and process the information, analyze the battery status, formulate an alarm plan based on the battery status, and send it to the monitoring alarm unit;

[0007] The monitoring alarm unit is used to issue alarms of different types and levels according to the alarm plan.

[0008] As a further improvement of the present technical solution, the sensor installed in the battery detection unit detects the information of the battery pack in real time, specifically including:

[0009] The sensors include a voltage sensor, a temperature sensor and a current sensor. The voltage sensor is used to detect the voltage of the battery pack, the temperature sensor is used to detect the temperature of the battery pack, and the current sensor is used to detect the current of the battery pack. The distributed layout formed by multiple sensors fully covers the battery pack, and the information is represented as the voltage, current and temperature of the battery pack.

[0010] As a further improvement of the present technical solution, the analysis and processing unit pre-processes the battery status of the target area, specifically including:

[0011] The voltage, current, and temperature data of the battery pack at a certain moment are collected by sensors to form a voltage, current, and temperature data set at a certain moment. The window size of the moving average filter is set to N, and the voltage, current, and temperature data set at a certain moment are processed by applying the moving average filter. That is, the voltage, current, and temperature data set at a certain moment are initialized into a queue with a length equal to the window size of the moving average filter. The newly collected battery status data is added to the end of the queue, and the data at the head of the queue is removed so that the amount of data in the queue remains at the window size. The average value of the data in the queue is calculated as the filtered voltage, current, and temperature at the current moment.

[0012] As a further improvement of the present technical solution, the analysis and processing unit uses a multi-sensor fusion method to assess the battery status level, specifically including:

[0013] Use voltage sensors, temperature sensors, and current sensors to collect the voltage, current, and temperature of the battery pack, respectively. Preprocess the collected data and analyze the processed voltage, current, and temperature data using a fusion algorithm to derive an estimated battery state.

[0014] Assume that the data collected by the voltage sensor is V, the data collected by the temperature sensor is T, the data collected by the current sensor is I, and the weight of the voltage sensor is W V , the weight of the temperature sensor is W T , the weight of the current sensor is W I , the battery state after fusion is calculated by the following formula:

[0015] S e =W V *V+W T *T+W I *I;

[0016] Set the battery status level threshold S yz , if the battery status S in the j time period e Less than S yz , it means that the battery status is normal. If the battery status S e Greater than Syz And less than 2S tz , it means that the battery state is in alert. If the battery state S e More than 2S yz , it means the battery status is in danger.

[0017] As a further improvement of the present technical solution, the analysis and processing unit formulates an alarm plan according to the battery status level, specifically including:

[0018] Solution (1): When the battery status is detected to be normal, a local voice prompt is triggered and a status notification is sent to the user's mobile device. The battery status changes are continuously monitored. If the battery status does not deteriorate within the j period of time, the prompt is automatically cancelled.

[0019] Solution (2): When the battery status reaches a critical level, a local moderate sound and light prompt is activated, with moderate sound intensity and slow light flashing frequency. At the same time, an early warning message is sent to the user's mobile device, and the battery status trend is predicted;

[0020] Solution (3): When the battery status is detected to be dangerous, a high-decibel sound and light alarm is immediately activated, with a harsh and continuous sound and strong flashing lights. A notification is sent to the user and emergency contacts, including a predicted battery status trend and risk assessment.

[0021] As a further improvement of the present technical solution, the prediction of the battery status trend in the above situation (2) specifically includes:

[0022] A system model is established, and a linear relationship is assumed between the smoke development trend and the battery status. The expression of the system model is:

[0023] X(k)=C*X(k-1)+D*u+w(k);

[0024] Among them, X(k) represents the state vector of the system at time k, C is the state transfer matrix, D is the external output matrix, u is the driving factor, w(k) is the process noise, and the battery state S is obtained through the sensor yc , the battery status level observation value Z(k) is obtained according to the battery status, and the observation model is established. The expression of the observation model is:

[0025] Z(k)=H*X(k)+v(K);

[0026] Update the prediction of battery status trend based on the system model and observation model, namely:

[0027] Q(k)=X(k)+K(k)(Z(k)-H(Q(k)));

[0028] Where Q(k) is the updated battery state trend prediction, X(k) is the predicted state, K(k) is the gain matrix, Z(k) is the observation value, and H is the observation matrix.

[0029] As a further improvement of this technical solution, the risk assessment in the solution (III) specifically includes:

[0030] If Q(k) reaches the dangerous battery status threshold within time period j, a high-decibel sound and light alarm will be immediately activated. The sound will be harsh and continuous, and the light will flash strongly. Notifications will be sent to the user and emergency contacts, and the risk will be assessed. Assuming that the battery status of solution (3) is Q(k) and the temperature is T, the risk factor is:

[0031] α=ω1*Q(k)+ω2*T;

[0032] Wherein, α represents the risk coefficient, ω1 and ω2 represent the weight coefficients of the impact of battery status and temperature on risk, and ω1+ω2=1.

[0033] As a further improvement of the present technical solution, the monitoring alarm unit issues alarms of different types and levels according to the alarm scheme, specifically including:

[0034] The monitoring alarm unit monitors the battery status of the battery pack in the target area in real time. When the battery status in the target area is low and has not deteriorated within the j time period, only a soft voice prompt is issued without an alarm. When the battery status in the target area is in an alert state, the battery status trend of the target area is continuously monitored. If the battery status has not deteriorated within the j time period and the battery status gradually improves over time, a local moderate sound and light prompt is issued. If the battery status deteriorates over time within the j time period and the battery status prediction value Q(k) exceeds the dangerous battery status threshold, a high-decibel sound and light alarm is immediately activated and the risk factor is evaluated, and the risk factor is sent to the user and emergency contact.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The analysis and processing unit calculates and analyzes the battery status based on the current, voltage, and temperature collected by the sensor, and grades the battery status according to the analysis results, so as to promptly detect abnormal battery conditions and take corresponding measures to avoid potential safety risks. By establishing a system model and an observation model to predict the battery status, possible battery failures can be predicted in advance. The prediction results are then integrated with the temperature inside the car for analysis to derive a risk coefficient, which is then sent to the user and emergency contacts to more accurately assess the potential battery failure risk and take measures in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1It is an overall block diagram of the present invention.

[0038] The meaning of each number in the figure is:

[0039] 1. Battery detection unit; 2. Analysis and processing unit; 3. Monitoring and alarm unit; DETAILED DESCRIPTION

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0041] Example 1

[0042] The present invention provides a new energy vehicle battery management system that matches the alarm scheme according to the battery status. Figure 1 As shown, it includes a battery detection unit 1, an analysis and processing unit 2, and a monitoring and alarm unit 3;

[0043] The battery detection unit 1 is used to detect the voltage, current and temperature information of the battery pack in real time through the installed sensors, and send this information to the analysis and processing unit 2; the analysis and processing unit 2 is used to receive the information of the battery pack, analyze and process this information, analyze the battery status, and formulate an alarm plan based on the battery status, and send it to the monitoring alarm unit 3; the monitoring alarm unit 3 is used to issue alarms of different types and levels according to the alarm plan.

[0044] The battery detection unit 1 collects the voltage, current and temperature information of the battery pack through sensors, so that the analysis and processing unit 2 can analyze the battery status of the battery pack. The analysis and processing unit 2 assigns weights to the voltage, current and temperature information of the battery pack to indicate the degree of influence of the voltage, current and temperature information of the battery pack on the battery status, and integrates them through mathematical formulas to more clearly understand the relationship between the voltage, current and temperature information of the battery pack and the battery status. By comparing the battery status with the battery status level threshold extracted from the database, the specific situation of the battery status of the battery pack is judged, so as to formulate a detailed graded alarm plan for the subsequent monitoring alarm unit 3. The monitoring alarm unit 3 determines which level of alarm plan to use according to the numerical changes in the battery status over a period of time, so that the user or emergency contact can understand the situation of the new energy vehicle at the first time, and judge whether the new energy vehicle can be self-rescued based on the risk assessment made by the monitoring alarm unit 3, thereby enhancing the safety of new energy vehicle users.

[0045] The sensors installed in the battery detection unit 1 detect the battery pack information in real time, including:

[0046] The sensors include voltage sensors, temperature sensors and current sensors. The voltage sensor is used to detect the voltage of the battery pack, the temperature sensor is used to detect the temperature of the battery pack, and the current sensor is used to detect the current of the battery pack. The distributed layout formed by multiple sensors fully covers the battery pack, and the information is expressed as the voltage, current and temperature of the battery pack.

[0047] The analysis and processing unit 2 pre-processes the battery pack information, specifically including:

[0048] The voltage, current and temperature data of the battery pack at a certain moment are collected by sensors to form a voltage, current and temperature data set at a certain moment. The window size of the moving average filter is set to N to find a balance between removing noise and maintaining data accuracy, so that the filtered voltage, current and temperature data can better reflect the actual battery status. The voltage, current and temperature data set at a certain moment is processed by applying the moving average filter to effectively reduce the random noise introduced in the measurement process. That is, the voltage, current and temperature data set at a certain moment is initialized to a queue with a length of the window size of the moving average filter. The newly collected battery status data is added to the end of the queue, and the data at the head of the queue is removed to keep the data amount in the queue at the window size. The average value of the data in the queue is calculated to reduce the influence of individual outliers or measurement errors on the results, thereby improving the accuracy of the data. The voltage, current and temperature processed as above are used as the filtered voltage, current and temperature at the current moment.

[0049] The analysis and processing unit 2 uses a multi-sensor fusion method to assess the battery status level, specifically including:

[0050] Use voltage sensors, temperature sensors, and current sensors to collect the voltage, current, and temperature of the battery pack, respectively. Preprocess the collected data and analyze the processed voltage, current, and temperature data using a fusion algorithm to derive an estimated battery state.

[0051] Assume that the data collected by the voltage sensor is V, the data collected by the temperature sensor is T, the data collected by the current sensor is I, and the weight of the voltage sensor is W V , the weight of the temperature sensor is W T , the weight of the current sensor is W I , the battery state after fusion is calculated by the following formula:

[0052] S e =W V *V+W T *T+W I *I;

[0053] The analysis and processing unit 2 formulates an alarm plan based on the battery status level, specifically including:

[0054] Set the battery status level threshold S yz , if the battery status S in the j time period e Less than S yz , it means the battery status is normal, start solution (1);

[0055] Solution (1): When the battery status is detected to be normal, a local voice prompt is triggered, allowing the user to immediately know the current good condition of the battery, enhancing the user's sense of security. A status notification is also sent to the user's mobile device, allowing the user to promptly understand the battery status even if they are not near the device, improving the timeliness of information transmission. The battery status changes are continuously monitored. If the battery status does not deteriorate within a period of time, the prompt is automatically canceled, avoiding unnecessary continuous prompts that disturb the user.

[0056] If the battery status S during the k time period e Greater than S yz And less than 2S yz , it means the battery status is in warning state, start plan (2);

[0057] Solution (2): When the battery status reaches a warning level, a local moderate sound and light prompt is activated with moderate sound intensity and slow flashing light frequency, so that users can immediately know that the battery status has reached a warning level. At the same time, an early warning message is sent to the user's mobile device, and the battery status trend is predicted to help users make better decisions.

[0058] The prediction of battery status trends in Solution (2) specifically includes:

[0059] A system model is established based on the linear relationship between the battery status development trend and the battery status level. The expression of the system model is:

[0060] X(k)=C*X(k-1)+D*u+w(k);

[0061] Among them, the above system model makes users more aware of the linear relationship between the battery status development trend and the battery status level. X(k) is represented as the state vector of the system at time k, C is the state transfer matrix, D is the external output matrix, u is the driving factor, w(k) is the process noise, and the battery status S is obtained through the sensor. e , the battery status level observation value Z(k) is obtained according to the battery status, and the observation model is established. The expression of the observation model is:

[0062] Z(k)=H*X(k(+v(K);

[0063] Update the prediction of battery status trend based on the system model and observation model, namely:

[0064] Q(k)=X(k)+K(k)(Z(k)-H(Q(k)));

[0065] Among them, the battery status trend is updated and predicted through the system model and observation model, which more comprehensively explains the development trend of the battery status. Q(k) is the updated battery status trend prediction, X(k) is the predicted state, K(k) is the gain matrix, Z(k) is the observation value, and H is the observation matrix

[0066] If the battery status S in the k time period e More than 2S yz , it means that the battery status is in danger, then start the plan (three);

[0067] Solution (3): When the battery status is detected to be dangerous, a high-decibel sound and light alarm is immediately activated, with a harsh and continuous sound and strong flashing lights. A notification is sent to the user and emergency contacts, including a predicted battery status trend and risk assessment.

[0068] Plan (III) includes a risk assessment, specifically:

[0069] If Q(k) reaches the dangerous battery status threshold within time period j, a high-decibel sound and light alarm will be immediately activated. The sound will be harsh and continuous, and the light will flash strongly. Notifications will be sent to the user and emergency contacts, and the risk will be assessed. Assuming that the battery status of solution (3) is Q(k) and the temperature is T, the risk factor is:

[0070] α=ω1*Q(k)+ω2*T;

[0071] Wherein, α represents the risk coefficient, ω1 and ω2 represent the weight coefficients of the impact of battery status and temperature on risk, and ω1+ω2=1.

[0072] The monitoring alarm unit 3 issues alarms of different types and levels according to the alarm plan, including:

[0073] The monitoring alarm unit 3 monitors the battery status of the battery pack in the target area in real time. When the battery status of the target area is low and has not deteriorated within the j time period, only a soft voice prompt is issued without an alarm. When the battery status of the target area is in an alert state, the battery status trend of the target area is continuously monitored. If the battery status has not deteriorated within the j time period and the battery status gradually improves over time, a local moderate sound and light prompt is issued. If the battery status deteriorates over time within the j time period, and the battery status prediction value Q(k) exceeds the dangerous battery status threshold, a high-decibel sound and light alarm is immediately activated and the risk factor is evaluated, and the risk factor is sent to the user and emergency contact.

[0074] The present invention collects the voltage, current and temperature information of the battery pack through sensors, and assigns weights to the voltage, current and temperature information of the battery pack to indicate the degree of influence of the voltage, current and temperature information of the battery pack on the battery status, and then integrates the voltage, current and temperature information of the battery pack through mathematical formulas to more clearly understand the relationship between the voltage, current and temperature information of the battery pack and the battery status, and judges the specific situation of the battery status of the battery pack by comparing the battery status with the battery status level threshold extracted from the database, so as to facilitate the formulation of a subsequent detailed graded alarm plan, and then determines which level of alarm plan to use according to the numerical change of the battery status over a period of time, so that the user or emergency contact can know the situation of the new energy vehicle at the first time, and allows the new energy vehicle user to judge whether to implement self-rescue for the new energy vehicle based on risk assessment, thereby enhancing the safety of new energy vehicle users.

[0075] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A new energy vehicle battery management system that matches an alarm scheme according to battery status, characterized in that: It comprises a battery detection unit (1), an analysis and processing unit (2), and a monitoring and alarm unit (3); The battery detection unit (1) is used to detect voltage, current and temperature information of the battery pack in real time through installed sensors, and send this information to the analysis and processing unit (2); The analysis and processing unit (2) is used to receive information from the battery pack, analyze and process the information, analyze the battery status, formulate an alarm plan based on the battery status, and send the alarm plan to the monitoring alarm unit (3); The monitoring alarm unit (3) is used to issue alarms of different types and levels according to the alarm scheme; The analysis and processing unit (2) calculates and analyzes the battery status based on the current, voltage, and temperature collected by the sensor, classifies the battery status based on the analysis results, predicts the battery status by establishing a system model and an observation model, and then integrates the prediction results with the temperature inside the car to analyze and obtain a risk coefficient, which is then sent to the user and emergency contacts; The analysis and processing unit (2) formulates an alarm plan according to the battery status level, specifically including: Solution (1): When the battery status is detected to be normal, a local voice prompt is triggered and a status notification is sent to the user's mobile device. The battery status changes are continuously monitored. If the battery status does not deteriorate within the j period of time, the prompt is automatically cancelled. Solution (2): When the battery status reaches a critical level, a local moderate sound and light prompt is activated, with moderate sound intensity and slow light flashing frequency. At the same time, an early warning message is sent to the user's mobile device, and the battery status trend is predicted; Solution (3): When a dangerous battery condition is detected, a high-decibel audible and visual alarm is immediately activated, with a harsh and continuous sound and strong flashing lights. Notifications are sent to the user and emergency contacts, including a predicted battery condition trend and risk assessment. The prediction of the battery status trend in the second solution specifically includes: A system model is established based on the linear relationship between the battery status development trend and the battery status level. The expression of the system model is: X(k)=C*X(k-1)+D*u+w(k); Among them, X(k) represents the state vector of the system at time k, X(k-1) represents the state vector of the system at time k-1, C is the state transfer matrix, D is the external output matrix, u is the driving factor, w(k) is the process noise, and the battery state S is obtained through the sensor e , the battery status level observation value Z(k) is obtained according to the battery status, and the observation model is established. The expression of the observation model is: Z(k)=H*X(k)+v(K); Update the prediction of battery status trend based on the system model and observation model, namely: Q(k)=x(k)+K(k)(Z(k)-H(Q(k))); Where Q(k) is the updated battery state trend forecast, x(k) is the predicted state, K(k) is the gain matrix, Z(k) is the observation value, and H is the observation matrix; The risk assessment in the above-mentioned plan (III) includes: If Q(k) reaches the dangerous battery status threshold within the j-time period, a high-decibel sound and light alarm will be immediately activated, with a harsh and continuous sound and strong flashing lights. Notifications will be sent to the user and emergency contacts, and the risk will be assessed. Assuming that the battery status trend forecast of solution (3) is Q(k) and the temperature is T, the risk factor is: α=ω1*Q(k)+ω2*T; Where α represents the risk coefficient, ω1 and ω2 represent the weight coefficients of the impact of battery status and temperature on risk, and ω1+ω2=1; The sensor installed in the battery detection unit (1) detects information of the battery pack in real time, specifically including: The sensors include a voltage sensor, a temperature sensor, and a current sensor. The voltage sensor is used to detect the voltage of the battery pack, the temperature sensor is used to detect the temperature of the battery pack, and the current sensor is used to detect the current of the battery pack. The distributed layout formed by the multiple sensors fully covers the battery pack, and the information is represented as the voltage, current, and temperature of the battery pack. The analysis and processing unit (2) pre-processes the information of the battery pack, specifically including: The voltage, current, and temperature data of the battery pack at a certain moment are collected through sensors to form a voltage, current, and temperature data set at that moment. The window size of the moving average filter is set to N. The filtered voltage, current, and temperature data can better reflect the actual battery status. The voltage, current, and temperature data set at a certain moment are processed by applying the moving average filter. That is, the voltage, current, and temperature data set at a certain moment are initialized into a queue with a length equal to the window size of the moving average filter. Newly collected battery status data is added to the end of the queue, and the data at the head of the queue is removed to keep the data volume in the queue at the window size. The average value of the data in the queue is calculated as the filtered voltage, current, and temperature at the current moment. The analysis and processing unit (2) uses a multi-sensor fusion method to assess the battery status level, specifically including: Use voltage sensors, temperature sensors, and current sensors to collect the voltage, current, and temperature of the battery pack, respectively. Preprocess the collected data and analyze the processed voltage, current, and temperature data using a fusion algorithm to derive an estimated battery state. Assume that the data collected by the voltage sensor is V, the data collected by the temperature sensor is T, the data collected by the current sensor is I, and the weight of the voltage sensor is W V , the weight of the temperature sensor is W T , the weight of the current sensor is W I , the battery state after fusion is calculated by the following formula: S e =W V *V+W T *T+W I *I; Set the battery status level threshold S yz , if the battery status S in the j time period e Less than S yz , it means that the battery status is normal. If the battery status S e Greater than S yz And less than 2S yz , it means that the battery status is in alert. If the battery status S e More than 2S yz , it means the battery status is in danger; The monitoring alarm unit (3) issues alarms of different types and levels according to the alarm scheme, specifically including: The monitoring alarm unit (3) monitors the battery status of the battery pack in the target area in real time. When the battery status of the target area is low and the battery status has not deteriorated within the j time period, only a soft voice prompt is issued without an alarm. When the battery status of the target area is in an alert state, the battery status trend of the target area is continuously monitored. If the battery status has not deteriorated within the j time period and the battery status gradually improves over time, a local moderate sound and light prompt is issued. If the battery status deteriorates over time within the j time period and the battery status trend prediction Q(k) exceeds the dangerous battery status threshold, a high-decibel sound and light alarm is immediately activated and a risk factor is evaluated, and the risk factor is sent to the user and emergency contact.

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