Temperature monitoring circuit, method, device and energy management system

Abstract

The application relates to the technical field of energy monitoring, in particular to a temperature monitoring circuit, method, device and energy management system. The circuit comprises a plurality of resistance type temperature sensors, the temperature sensors are arranged at temperature monitoring points with different heat capacity characteristics respectively, are used for monitoring the temperature of the corresponding monitoring points, and a sensor network is formed by the plurality of temperature sensors in parallel, and the plurality of temperature sensors have different temperature-electricity characteristics. A signal acquisition circuit is connected with the sensor network, is used for converting the equivalent resistance of the sensor network into a single analog signal output, a signal processing unit is connected with the output end of the signal acquisition circuit, is used for collecting the analog signal, and performs characteristic analysis on the analog signal to determine the temperature monitoring point with abnormal temperature rise. On the one hand, the problem that the complexity is high and the cost sharply rises with the number of monitoring points is solved, and on the other hand, the temperature states of a plurality of monitoring points with different heat capacities and response characteristics such as battery cells and welding points are distinguished.

Description

Technical Field

[0001] This application relates to the field of energy monitoring technology, and in particular to a temperature monitoring circuit, method, device and energy management system. Background Technology

[0002] Currently, in new energy vehicles and related power electronic devices, it is necessary to monitor the temperature of key components such as battery cells, solder joints, busbars, and power semiconductors to prevent thermal runaway. These temperature monitoring points have vastly different heat capacities and heating characteristics; for example, overheating of solder joints can occur within seconds, while cell temperature rise can be measured in minutes. Therefore, simultaneous real-time monitoring at multiple points is essential.

[0003] In related technologies, a temperature sensor and corresponding signal conditioning circuit are usually configured independently for each monitoring point, forming a "one point, one channel, one path" architecture. On the one hand, as the number of temperature monitoring points increases, the number of sensors and circuits also needs to increase, which leads to a sharp increase in hardware costs and complexity. On the other hand, each point usually uses the same temperature sensor, which is feasible when the system undergoes uniform and slow temperature rise, but it cannot effectively distinguish between temperature rise modes with different physical characteristics. For example, it is impossible to distinguish between rapid local overheating of solder joints and slow overall temperature rise caused by the environment. Similar sensor resistance changes may occur, and it is difficult to distinguish them based on the independent threshold judgment of each channel. This can easily lead to missed or false alarms of high-risk local hot spots. Summary of the Invention

[0004] In view of the above-mentioned shortcomings and deficiencies of the prior art, this application provides a temperature monitoring circuit, method, device and energy management system. The main purpose is to solve the problem that the hardware cost and circuit complexity increase sharply with the increase of monitoring points, and it is difficult to effectively distinguish the temperature rise mode of monitoring points with different heat capacity characteristics (such as local rapid overheating of solder joints and slow temperature rise of the battery cell as a whole), resulting in low accuracy of potential risk identification.

[0005] To achieve the above objectives, the main technical solutions adopted in this application include:

[0006] In a first aspect, embodiments of this application provide a temperature monitoring circuit, the circuit including a plurality of resistive temperature sensors, the temperature sensors being respectively disposed at temperature monitoring points with different thermal characteristics, for monitoring the temperature of the corresponding monitoring points; the circuit further includes:

[0007] The sensor network is composed of multiple temperature sensors connected in parallel, and the multiple temperature sensors have different temperature-electrical characteristics; wherein, the temperature sensors with different temperature-electrical characteristics have different effects on the equivalent resistance of the sensor network in different temperature ranges.

[0008] A signal acquisition circuit, connected to the sensor network, is used to convert the equivalent resistance of the sensor network into a single analog output signal;

[0009] The signal processing unit is connected to the output terminal of the signal acquisition circuit and is used to acquire the analog signal and perform feature analysis on the analog signal to determine the temperature monitoring point where the abnormal temperature rise occurs.

[0010] Optionally, the temperature sensors with different temperature-electrical characteristics are implemented by configuring different material constant B values.

[0011] Optionally, the signal acquisition circuit includes a reference resistor, which is connected in series with the sensor network between the power supply voltage and ground to form a voltage divider circuit, and the connection node between the reference resistor and the sensor network serves as the output node for outputting the analog signal.

[0012] Optionally, the resistance value of the reference resistor is configured to match the equivalent resistance value of the sensor network at a preset reference temperature point.

[0013] Secondly, embodiments of this application provide a temperature monitoring method, applied to the signal processing unit described in any one of the first aspects above; the method includes:

[0014] The discrete signal sequence is obtained by reading the single analog signal output from the signal acquisition circuit according to the preset acquisition cycle.

[0015] Multi-dimensional features are extracted from the discrete signal sequence; wherein, the multi-dimensional features are used to characterize the differential influence of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges;

[0016] The multi-dimensional features are matched in the fault feature library to determine the temperature monitoring point where abnormal temperature rise occurs; wherein, the fault feature library pre-defines the feature range corresponding to abnormal temperature rise at different temperature monitoring points.

[0017] Optionally, the multi-dimensional features include instantaneous voltage value, voltage change rate for characterizing average temperature rise rate, and voltage change acceleration for characterizing temperature rise trend;

[0018] The step of extracting multi-dimensional features from the discrete signal sequence includes: performing analog-to-digital conversion on the discrete signal sequence to obtain a discrete voltage sequence; performing digital low-pass filtering on the voltage difference between adjacent sampling points in the discrete voltage sequence to obtain the voltage change rate; and performing differential operation on multiple consecutive voltage change rate values ​​to obtain the voltage change acceleration.

[0019] Optionally, the step of matching the multi-dimensional features in the fault feature library to determine the temperature monitoring point where abnormal temperature rise occurs includes: forming a real-time state vector from the extracted instantaneous voltage value, voltage change rate, and voltage change acceleration; comparing the real-time state vector with the feature ranges pre-calibrated in the fault feature library corresponding to different monitoring points; and determining that an abnormal temperature rise has occurred at the monitoring point when the real-time state vector falls within the feature range corresponding to a certain monitoring point.

[0020] Optionally, after matching the multi-dimensional features in the fault feature database to determine the temperature monitoring point where the abnormal temperature rise occurs, the method further includes: matching the multi-dimensional features in the fault feature database to determine abnormal temperature rise information; the abnormal temperature rise information includes the location of the temperature monitoring point with the abnormal temperature rise and the abnormality level; and executing an early warning response based on the abnormality level; the early warning response includes at least one of data recording, audible and visual alarms, derating operation, current limiting protection, and emergency shutdown.

[0021] Thirdly, embodiments of this application provide a temperature monitoring device, comprising:

[0022] The reading unit is configured to read a single analog signal output by the signal acquisition circuit according to a preset acquisition cycle to obtain a discrete signal sequence;

[0023] An extraction unit is configured to extract multi-dimensional features from the discrete signal sequence; wherein the multi-dimensional features are used to characterize the differential influence of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges;

[0024] The matching unit is configured to match the multi-dimensional features in a fault feature library to determine the temperature monitoring point where an abnormal temperature rise occurs; wherein, the fault feature library pre-defines the feature range corresponding to different temperature monitoring points when an abnormal temperature rise occurs.

[0025] Fourthly, embodiments of this application provide an energy management system including a temperature monitoring circuit as described in any one of the first aspects, wherein the temperature monitoring circuit implements the temperature monitoring method as described in any one of the first aspects.

[0026] By employing the above technical solution, this application provides a temperature monitoring circuit, including multiple resistive temperature sensors. These temperature sensors are respectively positioned at temperature monitoring points with different thermal capacities to monitor the temperature of the corresponding monitoring points. The circuit further includes: a sensor network, composed of multiple temperature sensors connected in parallel, each possessing distinct temperature-electrical characteristics; wherein, temperature sensors with different temperature-electrical characteristics have varying effects on the equivalent resistance of the sensor network across different temperature ranges; a signal acquisition circuit, connected to the sensor network, converting the equivalent resistance of the sensor network into a single analog output signal; and a signal processing unit, connected to the output of the signal acquisition circuit, acquiring the analog signal and performing feature analysis on the analog signal to determine the temperature monitoring point where an abnormal temperature rise occurs. Compared to related technologies, this approach sets up temperature sensors with different temperature-resistance characteristics for temperature monitoring points with varying thermal capacities, and connects them in parallel to form a sensor network that outputs only a single analog signal. This solves the hardware resource redundancy, high system complexity, and rapidly increasing cost with the number of monitoring points caused by the need for independent sensors, independent signal conditioning circuits, and independent acquisition channels for each temperature monitoring point in related technologies. On the other hand, by utilizing the different effects of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges, and by performing feature analysis on a single analog signal, the temperature rise status of different temperature monitoring points characterized by the differential effects can be identified. Without increasing the number of physical channels, the temperature status of multiple monitoring points with different thermal capacities and response characteristics, such as battery cells and solder joints, can be distinguished. Attached Figure Description

[0027] Figure 1 A schematic diagram of a temperature monitoring circuit provided in an embodiment of this application;

[0028] Figure 2 A schematic flowchart of a temperature monitoring method provided in an embodiment of this application;

[0029] Figure 3 This is a schematic diagram of a temperature monitoring device provided in an embodiment of this application. Detailed Implementation

[0030] To better understand the above technical solutions, exemplary embodiments of this application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application can be understood more clearly and thoroughly, and that the scope of this application can be fully conveyed to those skilled in the art.

[0031] As mentioned in the background, temperature monitoring points are required in key components of new energy vehicles, such as battery cells, solder joints, busbars, and power semiconductors. Similarly, temperature monitoring is often implemented in industrial or household electrical equipment. Traditional methods use independent circuits for temperature monitoring, meaning each monitoring point has its own temperature sensor and corresponding monitoring circuit. The number of components increases with the number of monitoring points, leading to higher hardware costs and system complexity. Furthermore, while using the same sensor at each point is feasible when the system experiences a uniform, slow temperature rise, it cannot effectively distinguish between physically different temperature rise patterns. For example, if an abnormal temperature rise occurs at a monitoring point, traditional methods can only monitor the data but cannot identify whether the temperature rise is caused by an anomaly, thus overlooking potential safety hazards.

[0032] To address the problem of low accuracy in identifying potential risks due to the rapid increase in hardware cost and circuit complexity with the addition of monitoring points, and the difficulty in effectively distinguishing temperature rise patterns at monitoring points with different thermal capacities (such as rapid localized overheating of solder joints versus slow overall temperature rise of the battery cell), this application proposes a temperature monitoring circuit that can be applied to various fields such as energy management, thermal protection of industrial equipment, and temperature control of household appliances. Figure 1 As shown, the circuit includes multiple resistive temperature sensors, such as the negative temperature coefficient (NTC) resistive temperature sensors NTC-A, NTC-B, and NTC-C used in this embodiment. These temperature sensors are respectively set at temperature monitoring points with different heat capacity characteristics to monitor the temperature at the corresponding monitoring points. The circuit also includes:

[0033] Sensor networks, see reference Figure 1 101 in the model consists of multiple temperature sensors connected in parallel, and these multiple temperature sensors have different temperature-electrical characteristics; among them, the temperature sensors with different temperature-electrical characteristics have different effects on the equivalent resistance of the sensor network in different temperature ranges.

[0034] In this context, the number of multiple sensors is understood to be at least two. To reflect the general situation, this embodiment takes three temperature monitoring points with different thermal capacity characteristics as an example, and each temperature monitoring point is equipped with a corresponding temperature sensor, namely NTC-A, NTC-B and NTC-C. The temperature-electrical characteristics of the three temperature sensors are not the same.

[0035] The heat capacity characteristic of a temperature monitoring point refers to the amount of heat capacity of the corresponding part of the monitoring point and the speed of its temperature change response when heated. For example, parts with small heat capacity (such as solder joints) have a fast temperature rise rate, while parts with large heat capacity (such as battery cells) have a slow temperature rise rate.

[0036] The temperature-electrical characteristic of a temperature sensor refers to the relationship between its resistance and temperature. This relationship is determined by the sensor material and manufacturing process, specifically by different material constants (B values). More specifically, different temperature-electrical characteristics determine the sensor's sensitivity in different temperature ranges. For example, NTC-A, NTC-B, and NTC-C use different B values ​​to achieve different sensitivities in different temperature ranges. Here, B value refers to the material parameter of the NTC thermistor, uniformly based on (25 / 85), as shown in the following formula:

[0037]

[0038] Where R25 is the NTC nominal resistance at 25℃, R85 is the NTC nominal resistance at 85℃, and ln is the natural logarithm, characterizing the nonlinear relationship between resistance and temperature. For temperature sensors with higher B values, the slope of the temperature-resistance curve increases with the increase of B value, the resistance change is more drastic in the high-temperature region above 70℃, and the response to rapid temperature changes is stronger, making it suitable for monitoring points with small heat capacity and rapid overheating. For temperature sensors with lower B values, the temperature-resistance curve is flatter, the resistance change is more stable in the medium-low temperature region of 30~60℃, and the resistance to temperature drift is stronger, making it suitable for monitoring points with large heat capacity and slow temperature rise.

[0039] It should be noted that determining the corresponding B-value temperature sensor for temperature monitoring points with different thermal capacity characteristics can be achieved either by pre-configuring a correspondence or by using a threshold determination method. For example, in the temperature monitoring process of a battery module, there are three temperature monitoring points: the surface of the cell body, the busbar connection, and the terminal solder joint. The thermal capacity characteristics of these three monitoring points are different. For instance, the maximum operating temperature of the cell body surface is 55℃, so an NTC-A device with a B-value (25 / 85) of 3435K and a nominal resistance of 10kΩ at 25℃ is selected. At the busbar connection, since a pre-warning signal needs to be monitored, a temperature rise of approximately 75℃ needs to be monitored; therefore, an NTC-B device with a B-value of 3950K and a nominal resistance of 10kΩ at 25℃ is selected. The terminal solder joint needs to monitor rapid overheating between 80℃ and 120℃, with approximately 85℃ as the main monitoring range; therefore, an NTC-C device with a B-value of 4100K and a nominal resistance of 10kΩ at 25℃ is selected. Devices with corresponding B values ​​can be pre-configured, such as based on the maximum operating temperature (the temperature range to be monitored); alternatively, threshold settings can be used. For example, for temperature monitoring points where the thermal capacity parameter is less than the first parameter threshold and the response rate is lower than the first preset rate, an NTC-A device can be selected; for temperature monitoring points where the thermal capacity parameter is between the first and second parameter thresholds and the response rate is between the first and second preset rates, an NTC-B device can be selected; and for temperature monitoring points where the thermal capacity parameter is greater than the second parameter threshold and the response rate is greater than the second preset rate, an NTC-C device can be selected, where the first preset rate is less than the second preset rate and the first parameter threshold is less than the second parameter threshold.

[0040] Optionally, in this embodiment, the B-values ​​of temperature sensors with different temperature-electrical characteristics differ by more than 200K, thereby making the voltage change characteristics more distinguishable.

[0041] In addition, the circuit also includes:

[0042] For signal acquisition circuits, please refer to... Figure 1 103 in the diagram is connected to the sensor network and is used to convert the equivalent resistance of the sensor network into a single analog signal for the output.

[0043] Signal processing unit, please refer to Figure 1 104 in the circuit is connected to the output of the signal acquisition circuit. It is used to acquire analog signals and perform feature analysis on the analog signals to determine the temperature monitoring point where abnormal temperature rise occurs.

[0044] Optionally, the circuit also includes a reference resistor, which is connected in series with the sensor network between the supply voltage and ground to form a voltage divider circuit, which can be referenced. Figure 1In section 102, the connection node between the reference resistor and the sensor network serves as the output node for the analog signal. Furthermore, the resistance value of the reference resistor is configured to match the equivalent resistance value of the sensor network at a preset reference temperature point.

[0045] In this embodiment, the reference resistor is configured to match the equivalent resistance of the sensor network at a preset reference temperature, so that the output node operates within the high-sensitivity range of the voltage divider curve at the reference temperature. The high-sensitivity range refers to the analog signal operating near 25°C at the point where the slope of the voltage divider curve is maximum, thereby improving the sensitivity to the initial temperature rise.

[0046] A key characteristic of parallel circuits is that the total conductance is the sum of the conductances of each branch. When the resistance of a sensor drops sharply, its conductance increases sharply. This increased conductance significantly affects the total resistance, thus dominating the change in the overall network resistance. Consequently, temperature sensors with different temperature-electrical characteristics have varying effects on the equivalent resistance of the sensor network across different temperature ranges. Furthermore, when multiple NTC temperature sensors are connected in parallel, there is a total impedance... When the temperature at a certain monitoring point changes, the corresponding resistance value of the NTC changes. Due to significant changes in the nonlinear RT characteristics (such as a sharp drop in NTC resistance at high temperatures), It exhibits a "step-like" fluctuation, which in turn affects the output voltage of the voltage divider circuit. This produces a characteristic change. Here, Vref is the voltage across the reference resistor.

[0047] Next, referring to Table 1, examples will be given to illustrate the resistance values ​​of the three NTC temperature sensors at key temperature points.

[0048] Table 1

[0049]

[0050] The three sensors NTC-A, NTC-B, and NTC-C are connected in parallel to form a temperature sensor network. One end of this network is connected to the DC power supply VCC (3.3V in this example), and the other end is connected in series with a reference resistor R_ref and then grounded. According to the data in Table 1, the network's equivalent resistance at 25°C is approximately 9.1kΩ. Therefore, the resistance of R_ref is selected as 9.1kΩ or the standard 10kΩ, so that the voltage divider output node is in the high-sensitivity region of the voltage-temperature curve at room temperature.

[0051] As shown in the table, at 55°C, the resistance of NTC-A is approximately 96% of that of NTC-B, indicating that both contribute similarly to the equivalent resistance. However, at 85°C, the resistance of NTC-C is only 85% of that of NTC-A, making it dominant in the parallel network. This differentiated temperature resistance characteristic allows for distinguishable changes in the network's equivalent resistance as the temperature varies at different monitoring points.

[0052] With a reference resistor R_ref of 10kΩ and a supply voltage of 3.3V, at an ambient temperature of 25°C, the equivalent resistance of the sensor network is approximately 9.09kΩ, and the output node voltage V_out is approximately 1.65V. V_out will exhibit different characteristics when the temperature changes at different monitoring points:

[0053] Scenario 1: Uniform temperature rise

[0054] As the ambient temperature slowly and uniformly rises from 25°C to 50°C, the resistance of all sensors decreases synchronously and gradually, the network equivalent resistance decreases slowly, and V_out decreases slowly accordingly. During this process, the rate of voltage change (dV / dt) is small and stable.

[0055] Scenario 2: Localized rapid overheating

[0056] When the power device (NTC-C monitoring point) experiences a rapid temperature rise from 25°C to 85°C within seconds due to overload, the resistance of the high-B-value NTC-C drops dramatically. Because of its highest B-value, the NTC-C exhibits the greatest rate of resistance change in the high-temperature region. The surge in NTC-C conductance dominates the change in the equivalent resistance of the entire parallel network, causing V_out to plummet from 1.65V to approximately 0.68V in an extremely short time. During this process, the dV / dt value is extremely high, and the voltage drop shows a clear accelerating trend (d²V / dt² is positive).

[0057] It should be noted that the table above shows the differentiated impact on equivalent resistance within the high-sensitivity temperature range corresponding to the temperature sensor. This should not be simply interpreted as determining abnormal temperature rise or triggering an alarm based solely on resistance changes at the corresponding temperature. Instead, characteristic analysis of the data is required, and the judgment should be based on the rate and trend of change. For example, at 55°C, only when the signal, after characteristic analysis, exhibits a moderate rate of decline dominated by the NTC-A sensor, and the final voltage falls into the range corresponding to the 55°C anomaly, is an abnormal temperature rise in the battery cell determined.

[0058] Compared to related technologies, this embodiment sets up temperature sensors with different temperature-resistance characteristics for temperature monitoring points with different thermal capacities, and connects them in parallel to form a sensor network that outputs only a single analog signal. This solves the hardware problems of related technologies, which require independent sensors, signal conditioning circuits, and acquisition channels for each temperature monitoring point, resulting in hardware resource redundancy, high system complexity, and a sharp increase in cost with the number of monitoring points. Furthermore, by utilizing the different effects of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges, and through feature analysis of the single analog signal, the temperature rise state of different temperature monitoring points characterized by these different effects can be identified. Without increasing the number of physical channels, this achieves the differentiation of temperature states at multiple monitoring points with vastly different thermal capacities and response characteristics, such as battery cells and solder joints.

[0059] On the other hand, this embodiment also provides a temperature monitoring method, applied to the temperature monitoring circuit mentioned in any of the above embodiments. For example... Figure 2 As shown, the method includes:

[0060] S11: Read the single analog signal output by the signal acquisition circuit according to the preset acquisition cycle to obtain a discrete signal sequence.

[0061] In S11, the single analog signal output by the signal acquisition circuit is processed according to a preset acquisition period, such as 10ms, to obtain multiple discrete signal values, thereby forming a discrete signal sequence.

[0062] S12 extracts multi-dimensional features from discrete signal sequences.

[0063] After obtaining the discrete signal sequence, it needs to be converted into a voltage sequence for feature extraction, resulting in multi-dimensional features. These multi-dimensional features characterize the varying effects of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network across different temperature ranges. They include at least three core features: instantaneous voltage value V_now, voltage change rate Slope_avg, and voltage change acceleration Accel.

[0064] S13, match multi-dimensional features in the fault feature database to determine the temperature monitoring point where abnormal temperature rise occurs.

[0065] Then, based on multi-dimensional features, a match is performed in the fault feature database to determine the temperature monitoring points where abnormal temperature rises occur. The fault feature database pre-defines the feature ranges corresponding to abnormal temperature rises at different temperature monitoring points.

[0066] In this embodiment, a monitoring method applicable to the temperature monitoring circuit in the above embodiments is proposed. This method utilizes the differential influence of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges. By performing feature analysis on a single analog signal, the temperature rise status of different temperature monitoring points characterized by the differential influence can be identified.

[0067] Optionally, the multi-dimensional features include instantaneous voltage values, voltage change rate to characterize the average temperature rise rate, and voltage change acceleration to characterize the temperature rise trend. Extracting multi-dimensional features from the discrete signal sequence includes: performing analog-to-digital conversion on the discrete signal sequence to obtain a discrete voltage sequence; performing digital low-pass filtering on the voltage difference between adjacent sampling points in the discrete voltage sequence to obtain the voltage change rate; and performing differential operations on multiple consecutive voltage change rate values ​​to obtain the voltage change acceleration.

[0068] In this embodiment, the discrete signal sequence is first converted from analog to digital to obtain a discrete voltage sequence, from which the instantaneous voltage value can be obtained. Then, the voltage difference between continuous voltage sampling points is calculated (i.e., estimated by discretization using the first derivative dV / dt), and digital low-pass filtered (e.g., using first-order inertial filtering or sliding window averaging) is applied to obtain the voltage change rate, reflecting the average speed of temperature change. Based on this, the voltage change acceleration is obtained by performing a difference operation on multiple continuously calculated Slope_avg values ​​(i.e., estimated by discretization using the second derivative d²V / dt²), which is used to determine whether the temperature rise process is accelerating, constant, or decelerating. By performing time-domain analysis on the single signal output by the sensor network, its multi-dimensional features such as amplitude, rate (first derivative), and trend (second derivative) are extracted. Based on a pre-built signal feature-physical location mapping model, specific abnormal heat points are decoded, achieving accurate fault location under highly integrated hardware conditions.

[0069] Furthermore, the multi-dimensional features are matched in the fault feature library to determine the temperature monitoring point where the abnormal temperature rise occurs. This includes: forming a real-time state vector from the extracted instantaneous voltage value, voltage change rate, and voltage change acceleration; comparing the real-time state vector with the pre-calibrated feature ranges corresponding to different monitoring points in the fault feature library; and determining that an abnormal temperature rise has occurred at a monitoring point when the real-time state vector falls within the feature range corresponding to a certain monitoring point.

[0070] The real-time state vector can be represented as S = (V_now, Slope_avg, Accel). In this embodiment, the feature library defines the feature vector ranges for various typical modes through prior experiments or simulation calibration. For example, based on the resistance data in Table 1 and a circuit configuration with a reference resistance of 10kΩ and a supply voltage of 3.3V, the following example mode can be set:

[0071] 1: "Overall Gentle Warming" Mode:

[0072] For example, if V_now is in the range of 1.5V to 1.65V, and the absolute values ​​of Slope_avg and Accel are both less than 0.1 V / s, then it is determined that it is in the current mode.

[0073] 2: 55°C point anomaly (NTC-A dominant) mode:

[0074] For example, if V_now drops rapidly below 1.30V and Slope_avg exceeds the threshold Th1 (e.g., 0.5 V / s), it indicates a moderate rate of temperature rise.

[0075] 3: 75°C point anomaly (NTC-B dominant) mode:

[0076] For example, a rapid drop in V_now to below 0.85V and a slope_avg exceeding a higher threshold Th2 (such as 1.0 V / s) indicate a rapid temperature rise.

[0077] 4: 85°C point anomaly (NTC-C dominant) mode:

[0078] For example, if V_now drops sharply below 0.70V, Slope_avg exceeds the highest threshold Th3 (e.g., 1.5 V / s), and Accel is positive, it indicates an accelerated temperature rise.

[0079] 5: Sensor open circuit fault mode: V_now continuously approaches the power supply voltage of 3.3V.

[0080] 6: Sensor short circuit or network short circuit fault mode: V_now remains close to 0V.

[0081] When the real-time state vector S falls within the feature range corresponding to a certain abnormal pattern defined in the fault feature library, it is determined that an abnormal event matching that pattern has occurred. By pre-setting the fault feature library, it is possible to quickly match various abnormal temperature rise conditions, thereby identifying the abnormal situation.

[0082] Optionally, after matching the multi-dimensional features in the fault feature database to determine the temperature monitoring point where the abnormal temperature rise occurs, the method further includes: matching the multi-dimensional features in the fault feature database to determine the abnormal temperature rise information; the abnormal temperature rise information includes the location of the temperature monitoring point with the abnormal temperature rise and the abnormality level; and executing an early warning response based on the abnormality level; the early warning response includes at least one of data recording, audible and visual alarms, derating operation, current limiting protection, and emergency shutdown.

[0083] In this embodiment, abnormal temperature rise information can be obtained by matching multi-dimensional features in a fault feature database. This includes the location of temperature monitoring points with abnormal temperature rises, such as cell A, solder joint B, and power device C, as well as the corresponding abnormal conditions, such as overall temperature rise, local overheating, and sensor failure. The abnormality level can be set for different abnormal conditions. For example, for overall temperature rise, only logs may be recorded; for rapid overheating of solder joints, an audible and visual alarm will be triggered immediately; for rapid overheating of power devices, a command will be directly issued to trigger system protection measures, such as derating or emergency shutdown. After determining the specific monitoring point where the abnormal temperature rise occurs through feature matching, different levels of intervention measures are taken according to the severity of the abnormal temperature rise, thereby achieving accurate early warning and protection.

[0084] Through any of the above implementation methods, this embodiment utilizes only one voltage acquisition channel and one voltage divider circuit to achieve temperature status monitoring of three monitoring points with different thermal characteristics, and can effectively distinguish between overall temperature rise and local hot spots, thus achieving accurate early warning.

[0085] By utilizing the temperature monitoring circuit and corresponding temperature monitoring method provided in any of the above embodiments, this embodiment provides a temperature monitoring circuit based on the synergistic utilization of the nonlinear characteristics of temperature sensors. This circuit encodes the temperature status information of multiple points into a single, feature-rich analog signal by matching sensors with differentiated temperature sensitivities (such as different B values) to different monitoring points and constructing a parallel network, thereby overcoming the limitations of the traditional "one point, one channel" architecture.

[0086] Furthermore, a corresponding temperature monitoring method is provided. This method performs time-domain analysis on the aforementioned single signal, extracting multi-dimensional features such as its amplitude, rate (first derivative), and trend (second derivative). Based on a pre-built signal feature-physical location mapping model, it decodes specific abnormal heat points, achieving accurate fault location under highly integrated hardware conditions. Through the combination of hardware design and software analysis, a highly reliable and highly integrated temperature monitoring solution with both global temperature sensing and early accurate local hotspot location capabilities is provided for fields such as new energy vehicle battery systems and power electronic devices, with minimal complexity and cost.

[0087] Furthermore, as Figure 2The specific implementation of the method shown in this embodiment provides a temperature monitoring device, such as... Figure 3 As shown, the device includes:

[0088] The reading unit 301 is configured to read a single analog signal output by the signal acquisition circuit according to a preset acquisition cycle to obtain a discrete signal sequence;

[0089] Extraction unit 302 is configured to extract multi-dimensional features from the discrete signal sequence; wherein the multi-dimensional features are used to characterize the differential influence of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges;

[0090] The matching unit 303 is configured to match the multi-dimensional features in a fault feature library to determine the temperature monitoring point where an abnormal temperature rise occurs; wherein, the fault feature library pre-defines the feature range corresponding to different temperature monitoring points when an abnormal temperature rise occurs.

[0091] In a specific application scenario, the extraction unit 302 is further configured to perform analog-to-digital conversion on the discrete signal sequence to obtain a discrete voltage sequence; in the discrete voltage sequence, perform digital low-pass filtering on the voltage difference between adjacent sampling points to obtain the voltage change rate; and perform differential operation on multiple consecutive voltage change rate values ​​to obtain the voltage change acceleration.

[0092] In specific application scenarios, the matching unit 303 is further configured to form a real-time state vector from the extracted instantaneous voltage value, voltage change rate, and voltage change acceleration; compare the real-time state vector with the pre-calibrated feature ranges corresponding to different monitoring points in the fault feature library; and determine that an abnormal temperature rise has occurred at the monitoring point when the real-time state vector falls into the feature range corresponding to a certain monitoring point.

[0093] In specific application scenarios, the matching unit 303 is further configured to match the multi-dimensional features in the fault feature database to determine abnormal temperature rise information; the abnormal temperature rise information includes the location of the temperature monitoring point of the abnormal temperature rise and the abnormal level; and execute an early warning response according to the abnormal level; the early warning response includes at least one of data recording, audible and visual alarm, derating operation, current limiting protection and emergency shutdown.

[0094] It should be noted that other corresponding descriptions of the functional units involved in the temperature monitoring device provided in this embodiment can be found in [reference needed]. Figure 1 and Figure 2 The corresponding descriptions in [the document] will not be repeated here.

[0095] Based on the above, Figure 1 The circuit shown and Figure 2 The method shown, and Figure 3 To achieve the above objectives, in addition to the virtual device embodiment shown, this application also provides an energy management system, which includes, as shown in the example, an energy management system. Figure 1 The temperature monitoring circuit shown and Figure 2 The temperature monitoring method shown.

[0096] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented using software plus necessary general-purpose hardware platforms, or it can be implemented in hardware. By applying the solution of this embodiment, compared with related technologies, temperature sensors with different temperature-resistance characteristics are set for temperature monitoring points with different thermal capacity characteristics, and they are connected in parallel to form a sensor network that outputs only a single analog signal. This solves the problems of hardware resource redundancy, high system complexity, and cost increase with the number of monitoring points caused by setting up an independent sensor, independent signal conditioning circuit, and independent acquisition channel for each temperature monitoring point in related technologies. On the other hand, by utilizing the differential influence of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges, and by performing feature analysis on the single analog signal, the temperature rise state of different temperature monitoring points characterized by the differential influence can be identified. Without increasing the number of physical channels, the temperature state of multiple monitoring points with different thermal capacities and response characteristics, such as battery cells and solder joints, can be distinguished.

[0097] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0098] In the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0099] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make modifications, alterations, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A temperature monitoring circuit, characterized in that, The circuit includes multiple resistive temperature sensors, each positioned at a temperature monitoring point with different thermal characteristics, for monitoring the temperature at the corresponding monitoring point; the circuit also includes: The sensor network is composed of multiple temperature sensors connected in parallel, and the multiple temperature sensors have different temperature-electrical characteristics; wherein, the temperature sensors with different temperature-electrical characteristics have different effects on the equivalent resistance of the sensor network in different temperature ranges. A signal acquisition circuit, connected to the sensor network, is used to convert the equivalent resistance of the sensor network into a single analog output signal; The signal processing unit is connected to the output terminal of the signal acquisition circuit and is used to acquire the analog signal and perform feature analysis on the analog signal to determine the temperature monitoring point where the abnormal temperature rise occurs.

2. The temperature monitoring circuit according to claim 1, characterized in that, The temperature sensors with different temperature-electrical properties are achieved by configuring different material constant B values.

3. The temperature monitoring circuit according to claim 1, characterized in that, The signal acquisition circuit includes: A reference resistor is connected in series with the sensor network between the power supply voltage and ground to form a voltage divider circuit. The connection node between the reference resistor and the sensor network serves as the output node for outputting the analog signal.

4. The temperature monitoring circuit according to claim 3, characterized in that, The resistance value of the reference resistor is configured to match the equivalent resistance value of the sensor network at a preset reference temperature point.

5. A temperature monitoring method, characterized in that, The method is applied to a signal processing unit as described in any one of claims 1 to 4; the method includes: The discrete signal sequence is obtained by reading the single analog signal output from the signal acquisition circuit according to the preset acquisition cycle. Multi-dimensional features are extracted from the discrete signal sequence; wherein, the multi-dimensional features are used to characterize the differential influence of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges; The multi-dimensional features are matched in the fault feature library to determine the temperature monitoring point where abnormal temperature rise occurs; wherein, the fault feature library pre-defines the feature range corresponding to abnormal temperature rise at different temperature monitoring points.

6. The method according to claim 5, characterized in that, The multidimensional features include instantaneous voltage value, voltage change rate used to characterize the average temperature rise rate, and voltage change acceleration used to characterize the temperature rise trend. The extraction of multi-dimensional features from the discrete signal sequence includes: The discrete signal sequence is subjected to analog-to-digital conversion to obtain a discrete voltage sequence; In the discrete voltage sequence, the voltage difference between adjacent sampling points is subjected to digital low-pass filtering to obtain the voltage change rate; The voltage change acceleration is obtained by performing differential operations on multiple consecutive voltage change rate values.

7. The method according to claim 5, characterized in that, The step of matching the multi-dimensional features in the fault feature database to determine the temperature monitoring point where the abnormal temperature rise occurs includes: The extracted instantaneous voltage value, voltage change rate, and voltage change acceleration are combined to form a real-time state vector; The real-time state vector is compared with the pre-calibrated feature ranges corresponding to different monitoring points in the fault feature library; When the real-time state vector falls within the characteristic range corresponding to a certain monitoring point, it is determined that an abnormal temperature rise has occurred at that monitoring point.

8. The method according to claim 5, characterized in that, After matching the multi-dimensional features in the fault feature database to determine the temperature monitoring point where the abnormal temperature rise occurs, the method further includes: The multi-dimensional features are matched in the fault feature database to determine abnormal temperature rise information; the abnormal temperature rise information includes the location of the temperature monitoring point of the abnormal temperature rise and the abnormal level. Based on the anomaly level, an early warning response is executed; the early warning response includes at least one of data logging, audible and visual alarms, reduced operation, current limiting protection, and emergency shutdown.

9. A temperature monitoring device, characterized in that, include: The reading unit is configured to read a single analog signal output by the signal acquisition circuit according to a preset acquisition cycle to obtain a discrete signal sequence; An extraction unit is configured to extract multi-dimensional features from the discrete signal sequence; wherein the multi-dimensional features are used to characterize the differential influence of temperature sensors with different temperature-electrical characteristics on the equivalent resistance of the sensor network in different temperature ranges; The matching unit is configured to match the multi-dimensional features in a fault feature library to determine the temperature monitoring point where an abnormal temperature rise occurs; wherein, the fault feature library pre-defines the feature range corresponding to different temperature monitoring points when an abnormal temperature rise occurs.

10. An energy management system, characterized in that, The device includes a temperature monitoring circuit as described in any one of claims 1 to 4, wherein the temperature monitoring circuit implements the temperature monitoring method as described in any one of claims 5 to 8.

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