Battery parameter real-time monitoring system based on monomer sampling

Abstract

The invention relates to the technical field of battery management systems, and provides a battery parameter real-time monitoring system based on monomer sampling, which comprises a main control chip and a plurality of monomer sampling chips, and each monomer sampling chip is attached to the negative electrode end of a battery and is used for monitoring battery parameters in real time; each single sampling chip comprises an internal resistance monitoring unit with a built-in internal resistance prediction model and a temperature monitoring unit with an internal temperature prediction model. According to the invention, real-time online monitoring of the single battery is realized through the single sampling chip, and abnormal values of the temperature and internal resistance of the battery are pre-warned to monitor the thermal runaway or aging phenomenon of the battery; furthermore, a software algorithm is built in a single sampling chip to compensate and predict the internal temperature of the battery and the monitored internal resistance abnormal value of the battery according to the monitored external temperature, so that measurement errors caused by complex influence factors are eliminated, the measurement precision is improved, and the hardware cost is reduced; and the measurement data transmission precision is improved through double-line daisy chain or Bluetooth communication connection.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management systems, and in particular to a battery parameter real-time monitoring system based on single-cell sampling. Background Art

[0002] Battery thermal runaway is closely related to the battery temperature, and is accompanied by changes in parameters such as increased internal resistance, voltage fluctuations, gas generation, and increased pressure. These parameter changes provide a basis for battery thermal runaway warning and abnormal battery screening. Among them, changes in internal resistance also provide a basis for battery aging conditions.

[0003] At present, the battery BMS monitoring can only monitor the external temperature of the battery and the ambient temperature on the surface of the battery pack. However, there is a time delay between the external temperature of the battery and the change of the internal temperature of the battery. As a result, when the abnormal external temperature of the battery is detected, thermal runaway has often occurred, and it is impossible to effectively provide early warning and preventive measures. At present, the battery BMS monitoring can only monitor the voltage, and it is difficult to monitor the change of the internal resistance of each battery cell.

[0004] Due to the complexity of factors affecting battery temperature and internal resistance, the monitored parameter values ​​may occasionally fail, causing false alarms. For the abnormal changes in temperature and internal resistance of the monitored single cells, compensation and estimation are required to improve the measurement accuracy. Therefore, how to monitor the abnormal changes in parameters such as temperature and internal resistance of each battery in the battery pack in real time and perform monitoring value compensation and prediction to improve monitoring accuracy, thereby providing accurate early warning of possible thermal runaway of the battery pack or battery aging, has become a technical problem that needs to be solved. Summary of the invention

[0005] Based on the above situation, the main purpose of the present invention is to provide a real-time battery parameter monitoring system based on single cell sampling to monitor the temperature change and internal resistance change of single cells and to compensate and predict abnormal monitoring values ​​to improve monitoring accuracy.

[0006] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0007] The present invention provides a battery parameter real-time monitoring system based on single cell sampling, comprising a main control chip and a plurality of single cell sampling chips connected to the main control chip for communication, wherein each single cell sampling chip is mounted on the negative terminal of a battery for real-time monitoring of battery parameters, and the main control chip is used to make control instructions for battery group operation according to the real-time monitored battery parameters and communicate with a host computer; each single cell sampling chip is built-in with: an internal resistance monitoring unit for real-time monitoring of the internal resistance of the single cell battery, and a temperature monitoring unit for real-time monitoring of the temperature of the single cell battery; the internal resistance monitoring unit transmits the real-time internal resistance value of the single cell battery to the main control chip, and when the real-time internal resistance value is abnormal, the internal resistance monitoring unit starts a built-in internal resistance prediction model to compensate for the abnormal internal resistance value as the predicted value of the internal resistance of the single cell battery for abnormal judgment; the temperature monitoring unit transmits the real-time external temperature value of the single cell battery to the main control chip, and when the real-time external temperature value is abnormal, the temperature monitoring unit starts a built-in internal temperature prediction model to estimate the internal temperature value as the predicted value of the internal temperature of the single cell battery for abnormal judgment.

[0008] Furthermore, the internal resistance monitoring unit adopts a four-wire AC injection method, injects an AC current signal into the battery through a current injection loop, and measures the AC voltage signal generated at both ends of the battery through a signal measurement loop, so that the real-time internal resistance value of the battery can be calculated through the AC current signal and the AC voltage signal.

[0009] Furthermore, the internal resistance monitoring unit adopts a second-order generalized integration algorithm instead of a traditional RC bandpass filter to eliminate interference signals and inject different AC current frequencies for different batteries.

[0010] Furthermore, the second-order generalized integration algorithm generates two second-order generalized integrators by software programming to filter the input signal. When the injected AC current signal passes through the second-order generalized integrator, its frequency is filtered as a useful signal, while other frequency signals are effectively attenuated.

[0011] Furthermore, the internal resistance monitoring unit adopts a software algorithm to build in an internal resistance prediction model to compensate for the measurement accuracy of the real-time internal resistance value. The internal resistance prediction model adopts three parameters: AC current signal, AC voltage signal and internal temperature of the battery to perform multivariate regression prediction modeling of the real-time internal resistance value. When the real-time internal resistance value is judged to be abnormal, the AC current signal, AC voltage signal and internal temperature of the battery with an interval of N cycles from the real-time internal resistance value are obtained and brought into the internal resistance prediction model to obtain the internal resistance prediction value. If the internal resistance prediction value is within a preset normal threshold, it is judged that the real-time internal resistance value is a measurement inaccuracy, and the normal internal resistance prediction value is transmitted to the main control unit; if the internal resistance prediction value exceeds the preset normal threshold, it is judged that the corresponding single cell is abnormal, and a warning information is transmitted to the main control unit.

[0012] Furthermore, the temperature monitoring unit integrates two temperature sensors to collect the external temperature of the battery, and the temperature sensors have an exposed die pad to achieve good coupling between the single cell sampling chip and the single cell.

[0013] Furthermore, the temperature monitoring unit uses a software algorithm with a built-in internal temperature prediction model to predict the internal temperature of the battery based on the external temperature of the battery and the real-time internal resistance value. When the real-time external temperature is judged to be abnormal, the external temperature of the battery, the ambient temperature and the real-time internal resistance value are obtained and brought into the internal resistance prediction model to obtain the internal temperature prediction value. If the internal temperature prediction value is within a preset normal threshold, it is judged that the real-time external temperature is a measurement inaccuracy, and the normal internal temperature prediction value is transmitted to the main control unit; if the internal temperature prediction value exceeds the preset normal threshold, it is judged that the corresponding single cell is abnormal, and a warning information is transmitted to the main control unit.

[0014] Furthermore, after receiving the external temperature of the battery, the built-in internal temperature prediction model estimates the internal temperature of the battery for the first time according to the external temperature of the battery and the ambient temperature, and controls the second-order generalized integration algorithm according to the first internal temperature of the battery to inject the battery with a suitable AC current frequency to calculate the real-time internal resistance value of the battery, and estimates the internal temperature of the battery for the second time according to the relationship between the real-time internal resistance value fitted at the corresponding AC current frequency and the internal temperature of the battery, which is the internal temperature prediction value.

[0015] Furthermore, the communication connection mode adopted between a main control chip and each single sampling chip is a two-wire daisy chain cascade communication.

[0016] Preferably, a main control chip and each single sampling chip are respectively integrated with a Bluetooth module to achieve a Bluetooth communication connection between the main control chip and the single sampling chip.

[0017] The beneficial effects of the present invention include:

[0018] In the first aspect, the present invention realizes real-time online monitoring of single cells by setting a single cell sampling chip on the single cell to monitor the external temperature of the battery and injecting AC current into the battery to monitor the internal resistance of the battery, and warns of abnormal monitoring values ​​to monitor thermal runaway or aging of the battery and prevent accidents before they occur; in the second aspect, the present invention uses a built-in software algorithm on the single cell sampling chip to compensate and predict the abnormal values ​​of the internal temperature of the battery and the monitored internal resistance of the battery according to the monitored external temperature, eliminates measurement errors caused by complex influencing factors, improves measurement accuracy, and reduces hardware costs; in the third aspect, the present invention realizes communication between the single cell sampling chip and the main control chip through a two-wire daisy chain or Bluetooth communication method, reduces the interference of the wiring harness on the measurement accuracy, and improves the quality of monitoring data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the structure of a battery parameter real-time monitoring system provided by an embodiment of the present invention.

[0020] Figure 2 It is a principle diagram of measuring the internal resistance of a battery using a four-wire AC injection method provided in an embodiment of the present invention.

[0021] Figure 3 It is a structural schematic diagram of a two-wire daisy chain cascade communication provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The present invention is further described below in conjunction with the accompanying drawings and specific implementation methods.

[0023] During the use of battery packs, there will be problems such as inconsistent capacity, inconsistent capacity attenuation, and battery aging, which may lead to overcharging and over-discharging, and then cause thermal runaway safety risks. During the entire thermal runaway process, the internal resistance and temperature of the battery will change. By performing online real-time detection of the internal resistance and temperature and identifying the characteristics of the early thermal runaway internal resistance, early warnings can be made to effectively prevent the occurrence of thermal runaway. In order to achieve high-precision battery internal resistance and temperature detection and apply them to thermal runaway prediction and aging battery screening, this solution provides a battery parameter real-time monitoring system based on single-cell sampling. At present, the temperature monitoring of batteries mainly measures the external temperature of several points on the surface of the battery pack. If the abnormal change of the internal temperature of the battery is transmitted to the surface of the battery pack for several minutes, the temperature of the single cell cannot be monitored in real time, which will result in thermal runaway. The temperature warning is not issued until the thermal runaway has already occurred. Some researchers have tried to place a temperature monitoring device inside the battery to monitor the internal temperature of the battery. This method can monitor the internal temperature in real time, but it interferes with the battery and the temperature monitoring device is susceptible to chemical corrosion. This solution monitors the surface temperature of each battery's negative electrode and starts a software algorithm to predict the battery's internal temperature when the surface temperature is abnormal. The monitoring error data has been eliminated to improve the temperature monitoring accuracy. The change in the battery's internal resistance can reflect the changes in the battery, but there are technical difficulties in the real-time monitoring of the internal resistance of a single cell. This solution optimizes the AC injection method with less interference in internal resistance monitoring to collect the battery's internal resistance, and uses a software algorithm to combine the monitored battery temperature to compensate for the collected internal resistance value, thereby improving the accuracy of internal resistance monitoring.

[0024] Please refer to Figure 1In order to monitor the external temperature, internal temperature and internal resistance of a single cell in real time so as to give an early warning of abnormal values, the present invention provides a battery parameter real-time monitoring system based on single cell sampling, comprising a main control chip and a plurality of single cell sampling chips connected to the main control chip in communication, each single cell sampling chip is mounted on the negative terminal of a battery for real-time monitoring of battery parameters, and the main control chip is used to make control instructions for the operation of the battery pack according to the real-time monitored battery parameters and communicate with a host computer; each single cell sampling chip is built-in: an internal resistance monitoring unit for real-time monitoring of the internal resistance of the single cell, and a temperature monitoring unit for real-time monitoring of the temperature of the single cell; the internal resistance monitoring unit transmits the real-time internal resistance value of the single cell to the main control chip, and when the real-time internal resistance value is abnormal, the internal resistance monitoring unit starts the built-in internal resistance prediction model to compensate for the abnormal internal resistance value as the predicted value of the internal resistance of the single cell for abnormal judgment; the temperature monitoring unit transmits the real-time external temperature value of the single cell to the main control chip, and when the real-time external temperature value is abnormal, the temperature monitoring unit starts the built-in internal temperature prediction model to estimate the internal temperature value as the predicted value of the internal temperature of the single cell for abnormal judgment.

[0025] Specifically, at present, battery internal resistance monitoring is the biggest problem of the current battery detection system, which directly affects the effective use of battery capacity, reduces the safety and reliability of battery use, and makes the battery charge and discharge control lack of sufficient reference basis, which will eventually affect the performance and service life of the battery. At present, the accuracy of battery internal resistance detection is very high, and the safety hazards caused by detection errors must be reduced. The internal resistance of the battery under the charge and discharge state is one of the determining factors for solving the health of the battery, so the accuracy of the internal resistance value measurement has become particularly important. This scheme aims at the reasons that affect the accuracy of battery internal resistance measurement, proposes a scheme for battery internal resistance compensation and accuracy improvement, compensates the internal resistance value to predict the accurate internal resistance value, reduces the influence of internal resistance measurement error, and the wrong estimation of battery health status; promptly handles battery problems and improves the reliability of the power supply system. Compared with the surface temperature, the internal temperature of the battery has a greater impact on the battery performance and can better characterize the working state of the battery, but the internal temperature of the battery is difficult to obtain directly. This scheme proposes a new algorithm for predicting the internal temperature of the battery. The algorithm uses the battery surface temperature, ambient temperature and internal resistance value to estimate the internal temperature. Compared with the single-frequency measurement method, it has the advantages of high accuracy and wide measurement range.

[0026] In order to reduce the interference of internal resistance monitoring and improve the monitoring accuracy, the internal resistance monitoring unit adopts a four-wire AC injection method. An AC current signal is injected into the battery through the current injection loop, and the AC voltage signal generated at both ends of the battery is measured through the signal measurement loop. The real-time internal resistance value of the battery can be calculated through the AC current signal and the AC voltage signal.

[0027] Specifically, the AC injection method is a commonly used internal resistance detection method. It applies an AC current signal of a fixed frequency to the battery, measures the voltage value fed back from both ends of the battery, and subtracts the DC component. The internal resistance of the battery is obtained based on the ratio of the feedback voltage value to the injected current value. When the AC injection method is used to detect the internal resistance of the battery, the battery does not need to be taken offline, and real-time online detection of the internal resistance is achieved. The internal resistance of the battery is generally very small, usually only a few milliohms, and the resistance of the wire cannot be ignored at this time. In order to accurately measure the internal resistance of the battery and reduce the influence of the wire on the internal resistance detection, this scheme adopts a four-wire AC injection measurement method. Please refer to Figure 2 The four-wire measurement principle of the AC injection method is explained. Among them, R1, R2, R3, and R4 are the equivalent resistances of the four wires, V is the voltmeter, and A is the ammeter. When a fixed frequency detection current Is flows out of the battery, the current will generate a voltage drop on the internal resistance of the battery. Under ideal conditions, the resistance of the voltmeter is infinite. At this time, Is will not flow through R3 and R4. The voltmeter can only detect the voltage drop generated by Is on the internal resistance of the battery, so as to separate the current and voltage measurement lines. This eliminates the influence of the voltage drop caused by the wire resistance on the measured voltage. Therefore, the four-wire AC measurement method is selected to measure the internal resistance of the battery to improve the detection accuracy.

[0028] In order to accurately measure the battery internal resistance and effectively eliminate interference signals at the AC current frequency suitable for different battery inputs, the internal resistance monitoring unit uses a second-order generalized integration algorithm instead of the traditional RC bandpass filter to eliminate interference signals and inject different AC current frequencies for different batteries. The second-order generalized integration algorithm uses software programming to generate two second-order generalized integrators to filter the input signal. When the injected AC current signal passes through the second-order generalized integrator, its frequency is filtered as a useful signal, while other frequency signals are effectively attenuated.

[0029] Specifically, the existing technology often uses the AC injection method to measure the internal resistance of the battery. Conventionally, a 1KHZ AC current frequency signal is generated. After driving the coupling circuit, an AC signal with the same frequency and phase is generated on the battery. The AC voltage with the same frequency is generated through the battery impedance as the basic principle of measuring the internal resistance, and the internal resistance of the battery is accurately measured. After a series of conditioning including tiny signal processing, anti-interference filtering, and amplification is performed on the AC voltage signal fed back by the internal resistance, the measurement signal is optimized to achieve the hardware compensation measurement effect. The problem of large and inaccurate measurement of voltage signals in the cascade state of multiple batteries is solved through a hardware design solution. By analyzing the sampling error, analog circuit error, conversion error and other measurement errors of the internal resistance measurement, a corresponding hardware solution is proposed. Then, common battery pack types include: lead-acid battery packs, lithium-ion battery packs, and nickel-metal hydride battery packs. The AC battery frequencies adapted to these battery packs are not the same. The unified use of an AC frequency of 1KHZ results in low measurement accuracy. In addition, the common hardware design scheme leads to large size and high cost of monitoring equipment, which is not suitable for the single sampling chip used in this scheme. This scheme adopts a second-order generalized integration algorithm generated by a software algorithm built into the single sampling chip. On the one hand, it reduces the hardware cost, and on the other hand, it can inject the appropriate AC current frequency for different batteries and eliminate other frequency interference, thereby improving the measurement accuracy. For a single battery, its internal resistance is relatively high at the beginning of charging. Its value will slowly decrease before the gas is precipitated, and will temporarily rise until the gas begins to precipitate. This is because of the existence of polarization. When not charging, its internal resistance will continue to decrease for a period of time. The degree of discharge will also affect the internal resistance. The lead sulfate formed during discharge is a poor conductor, which increases the plate resistance. For example, when the lead-acid battery just starts to discharge, its internal resistance increases relatively slowly, but when the lead-acid battery is about to end its discharge, the internal resistance will increase sharply, and its value can reach two to three times that of the time when it was just discharged. Since the internal resistance of the battery is generally a small resistance value of milliohms, the requirements for sensitivity and anti-interference ability are relatively strong, so the measurement process is complicated. And there are many errors in its measurement, such as unexpected contact resistance, so a special method must be used to measure the internal resistance of the battery to solve the impact of these errors. The AC method injects a low-frequency AC signal with a stable amplitude into the battery, measures the low-frequency voltage at both ends of the battery, the low-frequency current W flowing through, and the phase difference between the two, and thus calculates the internal resistance of the battery. The measurement time using the AC method is extremely short, generally around 100ms; the measurement accuracy is high, the measurement error is generally between 1% and 2%, and it will not cause much damage to the battery itself. In actual measurements, since the internal resistance of the battery is very small, interference and noise will have a great effect on it, so it is very important to effectively suppress interference and noise and improve measurement accuracy in internal resistance measurement. When measuring the internal resistance of the battery, since the on-site equipment and the battery should be kept at a certain distance to prevent magnetic field interference during battery charging, a longer wire is generally used as the transmission line for collecting signals.Due to the complex working conditions on site, the wires may have problems such as different lengths and thicknesses. Since the internal resistance value is very small, the interference of the line resistance on the measurement of the internal resistance value when collecting signals is very large. To solve this problem, it is necessary to introduce a four-wire measurement method. The four-wire method is composed of a current source terminal crystal that supplies a rated current and a voltage detection port that detects a voltage drop. The test line connected to the voltage detection port of the measured resistor is not affected by the line resistance W of the measuring wire and the contact resistance because the input resistance of the voltmeter is very large and basically no current flows through it, so accurate measurement can be achieved. In order to solve the problem of sudden change in internal resistance, an internal resistance prediction method based on a multivariate linear regression prediction model is proposed. When an emergency occurs in the system, a reference predicted internal resistance value is provided, thereby playing a method of software compensation for internal resistance measurement, making the internal resistance measurement more accurate and avoiding unnecessary losses. This solution uses a multivariate nonlinear regression algorithm to perform multivariate regression prediction modeling on the internal resistance value through the above three independent variables, and transplants the model into the software program of the internal resistance measurement system, so that the internal resistance measurement system can determine whether the system has measurement inaccuracy under certain trigger conditions rather than whether the battery internal resistance has really increased, thereby compensating for the accuracy of the internal resistance measurement by means of a software algorithm.

[0030] The AC injection internal resistance detection method based on the second-order generalized integral algorithm extracts the AC signal of a specific frequency during the injection current measurement and weak voltage signal extraction process, and generates orthogonal components for signal amplitude calculation. This optimized AC injection method can achieve accurate, fast, and multi-frequency point battery series internal resistance detection.

[0031] Due to the complexity of the factors affecting the measured parameter values ​​of the battery, measurement errors may occasionally occur in the parameter measurement values. In order to eliminate the false alarms caused by the measurement errors, the internal resistance monitoring unit uses a software algorithm to build in an internal resistance prediction model to compensate for the measurement accuracy of the real-time internal resistance value. The internal resistance prediction model uses three parameters, namely, AC current signal, AC voltage signal and internal temperature of the battery, to perform multivariate regression prediction modeling of the real-time internal resistance value. When the real-time internal resistance value is judged to be abnormal, the AC current signal, AC voltage signal and internal temperature of the battery with an interval of N cycles from the real-time internal resistance value are obtained and brought into the internal resistance prediction model to obtain the internal resistance prediction value. If the internal resistance prediction value is within the preset normal threshold, the real-time internal resistance value is judged to be a measurement inaccuracy, and the normal internal resistance prediction value is transmitted to the main control unit; if the internal resistance prediction value exceeds the preset normal threshold, the corresponding single cell is judged to be abnormal, and a warning message is transmitted to the main control unit.

[0032] In order to effectively monitor the surface temperature of the single cell, the temperature monitoring unit integrates two temperature sensors to collect the external temperature of the battery, and the temperature sensor has an exposed die pad to achieve good coupling between the single sampling chip and the single cell.

[0033] In order to reduce measurement errors, false alarms and improve temperature measurement accuracy, the temperature monitoring unit uses a software algorithm to build in an internal temperature prediction model to predict the internal temperature of the battery based on the external temperature of the battery and the real-time internal resistance value. When the real-time external temperature is judged to be abnormal, the external temperature of the battery, the ambient temperature and the real-time internal resistance value are obtained and brought into the internal resistance prediction model to obtain the internal temperature prediction value. If the internal temperature prediction value is within the preset normal threshold, the real-time external temperature is judged to be inaccurate measurement, and the normal internal temperature prediction value is transmitted to the main control unit; if the internal temperature prediction value exceeds the preset normal threshold, the corresponding single cell is judged to be abnormal, and an early warning message is transmitted to the main control unit. After receiving the external temperature of the battery, the built-in internal temperature prediction model estimates the internal temperature of the battery for the first time according to the external temperature of the battery and the ambient temperature, controls the second-order generalized integral algorithm according to the first internal temperature of the battery to inject the battery with a suitable AC current frequency to calculate the real-time internal resistance value of the battery, and estimates the internal temperature of the battery for the second time according to the relationship between the fitted real-time internal resistance value and the internal temperature of the battery under the corresponding AC current frequency, which is the internal temperature prediction value.

[0034] Specifically, for the temperature test of the battery, a redundant design of dual temperature sensors is often used and compensated for each other. However, the temperature sensor can only monitor the surface temperature of the battery, and real-time monitoring and timely prediction of the internal temperature of the battery are the key to ensuring the normal operation of the battery and improving its service life. The internal resistance of the battery depends on the battery temperature to a certain extent. The relationship between battery temperature and internal resistance has been confirmed. This scheme makes a first estimate of the internal temperature, and then selects the best frequency at the temperature based on the estimated temperature. Finally, the current injection method is used to make a second estimate of the internal temperature. This algorithm can increase the range of temperature prediction and improve the accuracy of temperature prediction.

[0035] Since the internal resistance of the battery is very weak, a long wiring harness will have a greater impact on the measurement accuracy. Please refer to Figure 3 , a communication connection method with little influence of wiring harness is adopted to transmit data timely and accurately: the communication connection method adopted between a main control chip and each single sampling chip is a two-wire daisy chain cascade communication.

[0036] Specifically, the battery management system needs to cascade the main control chip with multiple single-cell sampling chips. After each electric single-cell sampling chip obtains the battery voltage, current, temperature and abnormal status of the corresponding battery cell, it needs to communicate and transmit data with the main control chip. This requires targeted communication circuits to ensure the accuracy of the main control chip's control of each single-cell sampling chip in the cascade and the data transmission. For example, for a battery pack with 96 cells in series, 96 single-cell sampling chips need to be cascaded to achieve it. The data communication between chips in this scheme adopts a half-duplex working mode, that is, the transmitted data can be transmitted in both directions of the twisted pair, but not at the same time. At the beginning of data transmission, the main control chip communicates with the single-cell sampling chip based on the SPI protocol. In the bottom-to-top write operation, differential transmission is performed through two lines. After the two-line daisy chain transmission, the data is transmitted to the main control chip. In the top-to-bottom read operation, the interface circuit also needs to complete the encoding-decoding data transmission process. The main control chip encodes the downlink signal and transmits it to the single-cell sampling chip. The two-wire daisy chain structure proposed in this solution can realize a fast, low-interference and more applicable daisy chain connection.

[0037] Preferably, in order to further reduce complex wiring and optimize the structure of the battery management system, the communication connection method adopted is: a Bluetooth module is integrated on a main control chip and each single sampling chip to realize Bluetooth communication connection between the main control chip and the single sampling chip.

[0038] Specifically, although the two-wire daisy chain achieves low interference, the wiring harness is still too long when there are many batteries in series. Based on the requirement of reducing the complexity of wiring, this solution considers using wireless connection to achieve inter-chip communication. Bluetooth technology plays an important role in inter-chip communication. The Bluetooth protocol stack allows devices to discover and establish connections through broadcast channels. After the connection is established, the devices can communicate data, where the broadcast channel is used to discover devices, establish connections and broadcast data, and the data channel is used for data communication between devices that have established connections. Bluetooth technology is also designed in terms of security to ensure the security of communication between devices. During the pairing process, the devices exchange pairing information, including security keys, which are saved on both devices so that they can easily connect or automatically reconnect without repeating the initial pairing process. In addition, Bluetooth technology also provides measures to prevent pairing with the wrong device, such as ensuring the correct connection by comparing the number strings displayed on the two devices or entering a PIN code. With the advancement of process technology and the improvement of chip integration, Bluetooth on-chip design has become a reality. With the rise of 3D IC and chiplet integration, Bluetooth technology is constantly evolving to adapt to new challenges and demands, providing more efficient solutions for inter-chip communication.

[0039] It should be noted that the battery parameter real-time monitoring system described in this solution also includes monitoring units such as voltage monitoring, AC impedance spectrum measurement and on-chip balancing integrated on the single-cell sampling chip.

[0040] For those skilled in the art, various other corresponding changes and deformations can be made according to the technical solutions and concepts described above, and all of these changes and deformations should fall within the protection scope of the claims of the present invention.

[0041] It should be noted that the above-described embodiments are only some embodiments of the present invention, rather than all embodiments. The singular forms "a", "the" and "it" used in the embodiments and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

Claims

1. A real-time monitoring system for battery parameters based on single-cell sampling, characterized in that: It includes a main control chip and several single sampling chips connected to the main control chip. Each single sampling chip is mounted on the negative terminal of a battery to monitor the battery parameters in real time. The main control chip is used to make control instructions for the battery pack according to the real-time monitored battery parameters and communicate with the host computer. Each single cell sampling chip is built-in: an internal resistance monitoring unit for real-time monitoring of the internal resistance of the single cell, and a temperature monitoring unit for real-time monitoring of the temperature of the single cell; The internal resistance monitoring unit transmits the real-time internal resistance value of the single cell to the main control chip. When the real-time internal resistance value is abnormal, the internal resistance monitoring unit starts the built-in internal resistance prediction model to compensate for the abnormal internal resistance value as the single cell internal resistance prediction value to judge the battery abnormality; The temperature monitoring unit transmits the real-time external temperature value of the single cell to the main control chip. When the real-time external temperature value is abnormal, the temperature monitoring unit starts the built-in internal temperature prediction model to estimate the internal temperature value and use it as the predicted value of the internal temperature of the single cell to judge the battery abnormality.

2. The battery parameter real-time monitoring system according to claim 1, characterized in that: The internal resistance monitoring unit adopts a four-wire AC injection method, injects an AC current signal into the battery through a current injection loop, and measures the AC voltage signal generated at both ends of the battery through a signal measurement loop, so that the real-time internal resistance value of the battery can be calculated through the AC current signal and the AC voltage signal.

3. The battery parameter real-time monitoring system according to claim 2, characterized in that: The internal resistance monitoring unit adopts a second-order generalized integration algorithm to replace the traditional RC bandpass filter to eliminate interference signals and inject different AC current frequencies for different batteries.

4. The battery parameter real-time monitoring system according to claim 3, characterized in that: The second-order generalized integration algorithm generates two second-order generalized integrators by software programming to filter the input signal. When the injected AC current signal passes through the second-order generalized integrator, its frequency is filtered as a useful signal, while other frequency signals are effectively attenuated.

5. The battery parameter real-time monitoring system according to claim 2, characterized in that: The internal resistance monitoring unit adopts a software algorithm to build in an internal resistance prediction model to compensate for the measurement accuracy of the real-time internal resistance value. The internal resistance prediction model adopts three parameters, namely, AC current signal, AC voltage signal and internal temperature of the battery, to perform multivariate regression prediction modeling of the real-time internal resistance value. When the real-time internal resistance value is judged to be abnormal, the AC current signal, AC voltage signal and internal temperature of the battery with an interval of N cycles from the real-time internal resistance value are obtained and brought into the internal resistance prediction model to obtain the internal resistance prediction value. If the internal resistance prediction value is within a preset normal threshold, it is judged that the real-time internal resistance value is a measurement inaccuracy, and the normal internal resistance prediction value is transmitted to the main control unit; if the internal resistance prediction value exceeds the preset normal threshold, it is judged that the corresponding single cell is abnormal, and a warning message is transmitted to the main control unit.

6. The battery parameter real-time monitoring system according to claim 2, characterized in that: The temperature monitoring unit integrates two temperature sensors to collect the external temperature of the battery, and the temperature sensors have exposed die pads to achieve good coupling between the single sampling chip and the single battery.

7. The battery parameter real-time monitoring system according to claim 6, characterized in that: The temperature monitoring unit adopts a software algorithm with a built-in internal temperature prediction model to predict the internal temperature of the battery based on the external temperature of the battery and the real-time internal resistance value. When the real-time external temperature is judged to be abnormal, the external temperature of the battery, the ambient temperature and the real-time internal resistance value are obtained and brought into the internal resistance prediction model to obtain the internal temperature prediction value. If the internal temperature prediction value is within a preset normal threshold, it is judged that the real-time external temperature is a measurement inaccuracy, and the normal internal temperature prediction value is transmitted to the main control unit; if the internal temperature prediction value exceeds the preset normal threshold, it is judged that the corresponding single cell is abnormal, and a warning message is transmitted to the main control unit.

8. The battery parameter real-time monitoring system according to claim 7, characterized in that: After receiving the external temperature of the battery, the internal temperature prediction model estimates the internal temperature of the battery for the first time according to the external temperature of the battery and the ambient temperature, controls the second-order generalized integration algorithm according to the first internal temperature of the battery to inject the battery with a suitable alternating current frequency to calculate the real-time internal resistance value of the battery, and estimates the internal temperature of the battery for the second time according to the relationship between the real-time internal resistance value fitted at the corresponding alternating current frequency and the internal temperature of the battery, which is the internal temperature prediction value.

9. The battery parameter real-time monitoring system according to claim 1, characterized in that: The communication connection mode adopted between the main control chip and each single sampling chip is two-wire daisy chain cascade communication.

10. The battery parameter real-time monitoring system according to claim 1, characterized in that: The main control chip and each single sampling chip are respectively integrated with a Bluetooth module to achieve a Bluetooth communication connection between the main control chip and the single sampling chip.

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