Testing apparatus and system for backup battery in emergency lighting

Abstract

A testing apparatus consisting of an adapter housing a controller 1 that executes a computer program that switches an emergency lighting fixture 5 from mains power to a backup battery 7 at predefined

Description

The present invention relates to the field of emergency lighting, in particular to a testing apparatus and system for a backup battery in emergency lighting. BACKGROUND Currently, some fire departments require that standalone emergency lights must be regularly tested and that batteries can provide illumination for at least n hours (for example, 2 hours) after a power outage. Traditional testing methods involve manual operations, such as turning off the power or pressing a test button, and then observing whether the light functions properly. This method is not only time-consuming and labor-intensive but also fails to predict when the batteries need to be replaced. Particularly in factories, shopping malls, or residential buildings, where numerous emergency lighting devices are installed, conducting regular manual inspections becomes a massive undertaking. In view of the above, the present application is hereby filed. SUMMARY The present invention discloses a testing apparatus and system for a backup battery in emergency lighting, aimed at addressing the inconveniences associated with manual testing of a vast number of backup batteries for emergency lighting located in factories, shopping malls, or residential buildings. A first embodiment of the present invention provides a testing apparatus for a backup battery in emergency lighting, including: an adapter configured between an emergency lighting fixture and the backup battery. Here, the adapter includes a controller configured therein, a wireless module electrically connected to a radio frequency terminal of the controller, and a current acquisition unit and a voltage acquisition unit which are electrically connected to an input terminal of the controller; and the controller is configured to execute a computer program stored therein to implement the steps of: switching the emergency lighting fixture from mains power to the backup battery at predefined intervals, and acquiring backup battery discharge data acquired by the current acquisition unit and the voltage acquisition unit, the discharge data including current time-series data and voltage time-series data; and invoking a pre-built battery health assessment model to predict the current time-series data and the voltage time-series data, resulting in the generation of a state of health (SOH) value of the backup battery and a backup battery replacement recommendation based on the SOH value, and then uploading the information to a terminal device via a wireless module. Preferably, the wireless module is at least one of a ZigBee module, a 4G / 5G module, a Bluetooth module, or a Wi-Fi module. Preferably, the testing apparatus further includes a switching circuit, where and a control terminal of the switching circuit is electrically connected to an output terminal of the controller, and the switching circuit is able to switch a power supply of the emergency lighting fixture based on control signals of the controller. Preferably, the switching circuit includes a relay; and a coil of the relay is electrically connected to the output terminal of the controller, a first set of contacts of the relay is used to connect the emergency lighting fixture and the backup battery, and a second set of contacts of the relay is used to connect the emergency lighting fixture and the mains power. Preferably, the testing apparatus further includes an inverter configured between the backup battery and the emergency lighting fixture, and a control terminal of the inverter is electrically connected to the output terminal of the controller. Preferably, the voltage acquisition unit is a voltage acquisition circuit connected in series between the backup battery and the emergency lighting fixture, and the current acquisition unit is a current transformer installed in a circuit connecting the backup battery and the emergency lighting fixture. Preferably, the battery health assessment model is a long short-term memory (LSTM) model trained based on historically acquired battery discharge data; and the training process includes: inputting historical data into the LSTM model to process time-series data, extracting time-related dynamic features, mapping the time-related dynamic features to generate an SOH value, computing the actual SOH value against the SOH value generated by mapping using a mean squared error (MSE) function, and adjusting the weights of the LSTM model based on computation results, the historical discharge data including: curves of voltage changing over time during the discharge process, curves of current changing over time during the discharge process, and corresponding SOH values. Preferably, the testing apparatus further includes: extracting a change trajectory of SOH values recorded in multiple tests, fitting same to the LSTM model, and using the current SOH value as an initial condition to predict a decline curve of the SOH values over future time periods. A second embodiment of the present invention provides a testing system for a backup battery in emergency lighting, including a cloud platform, a terminal device, and the testing apparatus for a backup battery in emergency lighting as described above, the controller is able to upload acquired data and processed data to the cloud platform, and the terminal device is able to access the cloud platform for data viewing. According to the testing apparatus and system for a backup battery in emergency lighting, a controller switches an emergency lighting fixture from mains power to a backup battery at predefined intervals, then invokes a pre-built battery health assessment model to predict current time-series data and voltage time-series data, resulting in the generation of an SOH value of the backup battery and a backup battery replacement recommendation based on the SOH value, and then uploads the information to a terminal device via a wireless module. This addresses the inconveniences associated with manual testing of a vast number of backup batteries for emergency lighting located in factories, shopping malls, or residential buildings. BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a modular schematic diagram of a testing apparatus for a backup battery in emergency lighting according to a first embodiment of the present invention; and FIG. 2 is a schematic diagram illustrating the execution flow of a controller according to a second embodiment of the present invention. DETAILED DESCRIPTION The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the drawings in the embodiments of the present invention. It is obvious that the described embodiments are only some of the embodiments of the present invention and are not all the embodiments thereof. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without inventive effort fall within the scope of the present invention. In order to better understand the technical solutions of the present invention, the embodiments of the present invention are described in detail below with reference to the accompanying drawings. Terms used in embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The singular forms “a / an” and “the” as used in the embodiments of the present invention and in the appended claims are also intended to include the plural forms, unless the context clearly dictates otherwise. It should be understood that the term “and / or” used herein is merely an association relationship that describes associated objects, and represents that there may be three kinds of relationships. For example, A and / or B may represent the following three cases: only A exists, both A and B exist, or only B exists. In addition, the slash “ / ” used herein generally indicates that associated objects are in an “or” relationship. Depending on the context, the word “if’ as used herein may be interpreted as “once”, or “when”, or “in response to determining that”, or “in response to detecting that.” Similarly, depending on the context, the phrases “if it is determined that” or “if it is detected that (a stated condition or event occurs)” can be interpreted as “when it is determined that” or “in response to determining that” or “when it is detected that” or “in response to detecting that (a stated condition or event occurs).” The reference to “first\ second” in the embodiment is merely to distinguish similar objects and does not represent a specific order for the objects, and it is to be understood that “first\ second” may be interchanged in a specific order or sequence if allowed. It should be understood that the objects distinguished by “first\second” are interchangeable where appropriate, such that the embodiments described herein can be implemented in an order other than those illustrated or described herein. Specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. The present invention discloses a testing apparatus and system for a backup battery 7 in emergency lighting, aimed at addressing the inconveniences associated with manual testing of a vast number of backup batteries 7 for emergency lighting located in factories, shopping malls, or residential buildings. Referring to FIG. 1, a first embodiment of the present invention provides a testing apparatus for a backup battery 7 in emergency lighting, including: an adapter configured between an emergency lighting fixture 5 and the backup battery 7. Here, the adapter includes a controller 1 configured therein, a wireless module 4 electrically connected to a radio frequency terminal of the controller 1, and a current acquisition unit 2 and a voltage acquisition unit 3 which are electrically connected to an input terminal of the controller 1. It should be noted that the vast number of backup batteries 7 for emergency lighting located in factories, shopping malls, or residential buildings must be able to operate continuously for 2 hours after the mains power is disconnected. Any backup battery 7 that lasts less than 2 hours needs to be replaced to avoid the problem of not being able to provide power to emergency lighting devices in critical situations. In this embodiment, an internal core of the adapter is a controller 1, which acts as the main processing unit responsible for coordinating the operation of various modules within the adapter and communicating with external devices. The radio frequency terminal of the controller 1 is directly electrically connected to the wireless module 4, enabling real-time data transmission with a cloud platform or other devices. This ensures that test data and control signals can be efficiently and reliably transmitted between the devices and the cloud platform. Further, the voltage acquisition unit 3 is a series voltage acquisition circuit, which is directly connected between the backup battery 7 and the emergency lighting fixture 5. The voltage acquisition unit can monitor the voltage changes of the backup battery 7 supplying power to the lighting fixture in real time, ensuring that the acquired voltage data is highly accurate while not affecting the normal power supply to the lighting fixture. The current acquisition unit 2 is a current transformer, which is installed in a circuit connecting the backup battery 7 and the emergency lighting fixture 5. The current transformer obtains the current magnitude in the circuit through the principle of induction, without direct contact with the circuit. This not only enhances the safety of current acquisition but also avoids any physical changes to the wiring of the lighting fixture and the backup battery 7. In actual operation, the acquisition units transmit acquired voltage and current signals to the controller 1 inside the adapter, and the controller 1 processes and analyzes the data. Further, the design of the wireless module 4 within the adapter is flexible and versatile, which may be at least one of a ZigBee module, a 4G / 5G module, a Bluetooth module, or a WiFi module. The specific choice of module or combination depends on the application scenario’s requirements for data transmission distance, rate, and power consumption. For instance, in environments requiring low power consumption and short-distance transmission, the ZigBee module may be prioritized; in scenarios needing wide-area coverage with high-speed transmission, the 4G / 5G module is more suitable; the Bluetooth module is ideal for close-range point-to-point communication, such as direct interaction between portable devices and lighting fixtures; and the Wi-Fi module, with its high-speed data transmission capability, is suitable for real-time monitoring and data uploading in local area network environments. Further, a switching circuit 8 is used to switch the power supply of the emergency lighting fixture 5 between the mains power and the backup battery 7, ensuring that the emergency lighting fixture 5 can automatically switch to an emergency mode powered by the backup battery 7 in the event of a mains power outage or failure. A control terminal of the switching circuit 8 is electrically connected to an output terminal of the controller 1, and the controller 1 triggers the power supply switching operation of the switching circuit 8 by sending control signals. Specifically, a relay is arranged inside the switching circuit 8, and a coil of the relay is electrically connected to the output terminal of controller 1. A first set of contacts of the relay connects the backup battery 7 and the emergency lighting fixture 5. In response to the controller 1 issuing a switching command, the relay activates the first set of contacts, allowing the emergency lighting fixture 5 to draw power from the backup battery 7. Under normal conditions where the mains power is available, the relay remains in a default state, with a second set of contacts connecting the mains power and the emergency lighting fixture 5, ensuring that the lighting fixture is powered by the mains power. In response to the mains power being interrupted or the controller 1 detecting the need to switch to an emergency mode, the controller 1 sends a control signal to the relay, energizing the coil of the relay and closing the first set of contacts, thus switching to the backup battery 7 for power supply. Further, an inverter 6 is arranged between the backup battery 7 and the emergency lighting fixture 5 to convert direct current provided by the backup battery 7 into alternating current suitable for use by the emergency lighting fixture 5. A control terminal of the inverter 6 is electrically connected to the output terminal of the controller 1, and an operational status of the inverter is managed by control signals issued by the controller 1. In cases of normal mains power supply, the emergency lighting fixture 5 typically operates directly from the mains power, while the inverter 6 remains in a standby mode and does not engage in power transmission. However, when the mains power is interrupted or during emergency testing, the controller 1 detects the change in power supply status and sends a start signal to the control terminal of the inverter 6, activating the inverter 6. The inverter 6 then begins operation, converting the direct current from the backup battery 7 into alternating current, providing stable power to the emergency lighting fixture 5 to ensure that a lighting system functions normally during a mains power interruption. Referring to FIG. 2, the controller 1 is configured to execute a computer program stored therein to implement the following steps. At S101, the emergency lighting fixture 5 is switched from mains power to the backup battery 7 at predefined intervals, and backup battery 7 discharge data acquired by the current acquisition unit 2 and the voltage acquisition unit 3 is acquired. Here, the discharge data includes current time-series data and voltage time-series data. It should be noted that, through the established control logic, the power supply for the emergency lighting fixture 5 is automatically switched from the mains power to the backup battery 7 at predefined time intervals (such as weekly or monthly) to conduct battery discharge tests. The switching operation is controlled by the controller 1, which activates the switching circuit 8 by outputting control signals, disconnecting the emergency lighting fixture 5 from the mains power and switching to power supply from the backup battery 7. Once the switch is complete, the backup battery 7 begins to provide power to the emergency lighting fixture 5, simulating the actual operating conditions during an emergency power outage. During this process, the current acquisition unit 2 and the voltage acquisition unit 3 monitor the discharge status of the backup battery 7 in real time, collecting current time-series data and voltage timeseries data during the battery discharge process. The data is dynamic parameters recorded in chronological order, reflecting the variations in current and voltage during the battery discharge. For example, the current acquisition unit 2 senses the real-time discharge current using a current transformer arranged in the circuit, and the voltage acquisition unit 3 measures the dynamic changes in battery output voltage through a voltage acquisition circuit connected in series between the backup battery 7 and the lighting fixture. At S102, a pre-built battery health assessment model is invoked to predict the current timeseries data and the voltage time-series data, resulting in the generation of an SOH value of the backup battery 7 and a backup battery 7 replacement recommendation based on the SOH value, and then the information is uploaded to a terminal device via a wireless module 4. After completing the discharge test of the backup battery 7 and collecting complete current time-series data and voltage time-series data, the controller 1 invokes a pre-built battery health assessment model to process and analyze the data. The model, developed based on historical training data, correlates the dynamic features of the backup battery 7 during the discharge process with its state of health (SOH) to evaluate the current health level of the battery. Specifically, after inputting the current and voltage time-series data into the assessment model, the model first extracts features from the data, identifying key parameters that reflect battery performance, such as voltage decay rate, current fluctuation amplitude, and trends in power change during discharge. The parameters are then input into the core computation logic of the model, to be compared against preset health assessment indicators (such as nominal capacity and nominal discharge efficiency) to calculate the current SOH value of the battery. The SOH value is typically expressed as a percentage, reflecting the proportion of the actual performance of the battery relative to that of a new battery. For example, an SOH value of 85% indicates that the current ability of the battery to store and release energy is 85% of its capacity when new. Once the SOH value is calculated, the system generates battery replacement recommendations based on predefined replacement criteria. For instance, in response to the SOH value falling below a set warning threshold (such as 60%), the system will generate a maintenance alert stating “Battery replacement recommended”; and in response to the SOH value being within a safe range, the system will generate a prompt saying “Battery status normal, no replacement needed”. To enable real-time monitoring and remote management, these calculation results, including the SOH value and replacement recommendations, are uploaded to a user terminal or cloud management platform via the wireless module 4 within the controller 1. Users can view a battery health status report through a mobile application or backend system and schedule maintenance operations based on the replacement recommendations. In a possible embodiment of the present invention, the battery health assessment model is constructed using an LSTM neural network, leveraging its ability to process time-series data to analyze battery discharge data and generate an SOH value that reflects the current health status of the battery. The model is trained based on historically acquired battery discharge data, which includes curves of voltage changing over time during the discharge process, curves of current changing over time during the discharge process, and corresponding SOH values for each discharge event, used to establish the correlation between input features and target outputs. At the start of the training process, the acquired historical data is input into the LSTM model, which captures the dynamic features of the time-series data through its unique structure, including the variation trends and fluctuations in voltage and current overtime during discharge, along with their potential relationships with the battery health status. Through memory and forgetting mechanisms, an LSTM unit focuses on the voltage and current change features at critical moments during the discharge process, while ignoring noise information unrelated to battery health. After extracting the time-related dynamic features, these features are mapped to a target output SOH value, generating a model predicted value. Subsequently, the predicted SOH value is compared with the corresponding actual SOH value to calculate the discrepancy between the two. Errors are calculated based on an MSE loss function, which amplifies large deviations by squaring the errors, ensuring that the model can more accurately fit the SOH value. To optimize the performance of the model, in the training process, error values are utilized to adjust the weights of the LSTM model through backpropagation, reducing the error values through multiple iterations and gradually improving the predictive capability of the model. Based on the training process described above, the LSTM model can accurately capture time-series patterns in the discharge data and identify the health characteristics of the battery under different usage conditions. This enables the model to infer the current SOH value from newly collected discharge data and supports further health assessment and lifespan prediction. The training of the model allows it to adapt to various battery types and discharge environments, providing intelligent support for battery status evaluation. In a possible implementation of the present invention, the testing apparatus for a backup battery in emergency lighting further includes: extracting a change trajectory of SOH values recorded in multiple tests, fitting same to the LSTM model, and using the current SOH value as an initial condition to predict a decline curve of the SOH values over future time periods. It should be noted that the SOH values recorded from multiple tests are stored in a timeseries format, reflecting the degradation patterns of the battery over long-term use. This includes the gradual decline trend of the SOH values over time, as well as any potential nonlinear characteristics or phased degradation patterns. The LSTM model, leveraging its ability to process time-series data, can learn the dynamic variation patterns within these historical trajectories and construct a model capable of predicting future changes in SOH values. In practical application, the current SOH value serves as an initial condition input for the LSTM model, which, combined with the SOH change patterns learned during training, begins to predict the variation trend of battery SOH values over future time periods. A memory unit of the LSTM model dynamically combines the initial SOH value with the historical trajectory features stored in the model to generate a predicted SOH value decline curve. This curve not only reflects the overall trend of SOH value degradation over time but also captures critical points in the degradation process, such as phases where the health status suddenly declines rapidly. In this way, the model can accurately predict the remaining lifespan and future health status of the battery, providing users with precise recommendations for battery replacement timing. A second embodiment of the present invention provides a testing system for a backup battery in emergency lighting, including a cloud platform, a terminal device, and the testing apparatus for a backup battery in emergency lighting as described above, the controller is able to upload acquired data and processed data to the cloud platform, and the terminal device is able to access the cloud platform for data viewing. According to the testing apparatus and system for a backup battery in emergency lighting, a controller switches an emergency lighting fixture from mains power to a backup battery at predefined intervals, then invokes a pre-built battery health assessment model to predict current time-series data and voltage time-series data, resulting in the generation of an SOH value of the backup battery and a backup battery replacement recommendation based on the SOH value, and then uploads the information to a terminal device via a wireless module. This addresses the inconveniences associated with manual testing of a vast number of backup batteries for emergency lighting located in factories, shopping malls, or residential buildings. Only a preferred embodiment of the present invention is described above, and the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be readily conceived by those skilled in the art within the technical scope disclosed by the present invention shall fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be subject to the scope of protection of the claims.

Claims

1. A testing apparatus for a backup battery in emergency lighting, comprising: an adapter configured between an emergency lighting fixture and the backup battery, wherein the adapter comprises a controller configured therein, a wireless module electrically connected to a radio frequency terminal of the controller, and a current acquisition unit and a voltage acquisition unit which are electrically connected to an input terminal of the controller; andthe controller is configured to execute a computer program stored therein to implement the steps of:switching the emergency lighting fixture from mains power to the backup battery at predefined intervals, and acquiring backup battery discharge data acquired by the current acquisition unit and the voltage acquisition unit, the discharge data comprising current timeseries data and voltage time-series data; andinvoking a pre-built battery health assessment model to predict the current time-series data and the voltage time-series data, resulting in the generation of a state of health (SOH) value of the backup battery and a backup battery replacement recommendation based on the SOH value, and then uploading the information to a terminal device via a wireless module.

2. The testing apparatus for a backup battery in emergency lighting of claim 1, wherein the wireless module is at least one of a ZigBee module, a 4G / 5G module, a Bluetooth module, or a Wi-Fi module.

3. The testing apparatus for a backup battery in emergency lighting of claim 1, further comprising: a switching circuit;wherein a control terminal of the switching circuit is electrically connected to an output terminal of the controller, and the switching circuit is able to switch a power supply of the emergency lighting fixture based on control signals of the controller.

4. The testing apparatus for a backup battery in emergency lighting of claim 3, wherein the switching circuit comprises a relay;and a coil of the relay is electrically connected to the output terminal of the controller, a first set of contacts of the relay is used to connect the emergency lighting fixture and the backupbattery, and a second set of contacts of the relay is used to connect the emergency lighting fixture and the mains power.

5. The testing apparatus for a backup battery in emergency lighting of claim 4, further comprising an inverter configured between the backup battery and the emergency lighting fixture, wherein a control terminal of the inverter is electrically connected to the output terminal of the controller.

6. The testing apparatus for a backup battery in emergency lighting of claim 4, wherein the voltage acquisition unit is a voltage acquisition circuit connected in series between the backup battery and the emergency lighting fixture, and the current acquisition unit is a current transformer installed in a circuit connecting the backup battery and the emergency lighting fixture.

7. The testing apparatus for a backup battery in emergency lighting of claim 1, wherein the battery health assessment model is a long short-term memory (LSTM) model trained based on historically acquired battery discharge data; and the training process comprises:inputting historical data into the LSTM model to process time-series data, extracting time-related dynamic features, mapping the time-related dynamic features to generate an SOH value, computing the actual SOH value against the SOH value generated by mapping using a mean squared error (MSE) function, and adjusting the weights of the LSTM model based on computation results, the historical discharge data comprising: curves of voltage changing over time during the discharge process, curves of current changing over time during the discharge process, and corresponding SOH values.

8. The testing apparatus for a backup battery in emergency lighting of claim 7, further comprising: extracting a change trajectory of SOH values recorded in multiple tests, fitting same to the LSTM model, and using the current SOH value as an initial condition to predict a decline curve of the SOH values over future time periods.

9. A testing system for a backup battery in emergency lighting, comprising a cloud platform, a terminal device, and the testing apparatus for a backup battery in emergency lighting of any one of claims 1 to 8, wherein the controller is able to upload acquired data and processed data to the cloud platform, and the terminal device is able to access the cloud platform for data viewing.A

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