Description:Batteries consist of several individual storage cells that are electrically connected. Typically, each cell has a voltage potential of about 2.1 volts. By connecting cells in series, the voltages of the individual cells are cumulatively increased. For example, a typical car battery uses six battery cells to produce a total voltage of 12.6 volts when the battery is fully charged. If one cell is defective, the battery pack will not register more than 10.5 volts. The worst scenario is the battery can also fail. A dead battery is the most common type of failure.
The proposed innovation aims to improve the detection of damaged cells with an approach in which a mathematical model is combined with a sensor unit. The purpose of this invention is to identify a battery cell that is defective or impaired. This design can be implemented with minimal additional hardware, this method leverages existing battery management systems (BMS), making it cost-effective and scalable.
The system require:
1. Integrated Sensor Array: Utilizing a combination of voltage, temperature, and pressure sensors, this method collects comprehensive data from each cell in real-time.
2. User-Friendly Interface: An intuitive interface provides clear diagnostics and actionable insights to technicians and end-users, facilitating easy identification and replacement of defective cells.
The detection method according to the present invention enables the safe, simple and reliable detection of malfunctioning batteries in a battery pack, avoiding the disadvantages presented in the known technique, because it does not cause confusion, especially in the case of natural self-discharge.
The main features of the method according to the invention include the following steps:
Step1: - Measure the open-circuit voltage at the terminal of each battery cell (As per the fig.1)
Step 2: -Calculate the difference between the mean value of no-load measured voltage at the cell terminal and the measured no load voltage of battery pack (As per the fig.2).
Step 3: -Checking the difference and comparing it to the healthy battery pack voltage difference (As per the fig.3).
Step 4: - Detecting a faulty cell when the difference is greater than zero (As per the fig.4),.
As a result, this technique allows for individual testing of every cell in the battery, ensuring that at least one cell fails accurately. It is based on a comparison of the calculated deviation between the cell no-load voltage measurement and the average no-load voltage of each cell..

THE PRESENT INVENTION HAS SEVERAL ADVANTAGES:
1. The detection method according to the present invention enables the safe, simple and reliable detection of damaged battery elements, avoiding the disadvantages of the known technique, because it does not cause confusion, especially in the case of natural self-discharge.
2. This method allows individual testing of each cell that makes up the battery, so that an actual failure can be detected in at least one cell. The analysis relies on comparing the no-load voltage of different batteries and considering the average no–load current of each cell, which is adjusted with a variable proportional to the mean deviation. Therefore, the tests utilized to identify a legitimate battery malfunction are more accurate and thorough than simply appraising how cell states change over time.
3. The method according to the invention includes a warning step when a defective cell is detected. Specifically, if a defective element is detected, measures are applied to prevent the battery from charging. In the warning phase, an alarm signal belonging to the operator of the warning phase is preferably used.
4. The detection method of the invention preferably includes the action of stopping the battery from charging when at least one defective component is identified. The detection of a defective element in this manner indicates that the battery cannot be charged, necessitating specialized expertise for replacing the affected component.
The condition of the cells deteriorates when the batteries are used frequently. Cell voltages will diverge from their nominal values and the cells will lose their ability to store energy as a result. That means that a battery could contain damaged cells. The battery must be kept in a high state of health in order to be able to run for the entire anticipated lifetime while performing as expected. This requires the identification of such damaged cells. This requires the availability of precise techniques for identifying the battery's damaged cells.
Identifying defective cells in battery packs is critical to the safety, performance and longevity of battery devices. Although current methods provide some degree of detection, their accuracy, responsiveness and cost-effectiveness are often lower. Combining advanced sensors with machine learning and predictive analytics, the proposed approach will revolutionize the identification process. By obtaining a patent for this method, we can establish 'the new standard of battery management' and ensure safer, more efficient energy storage options in the future.

The steps to check a defective cell in a battery pack:
1. Start with the monitoring of the No-load Voltage of the battery pack.
Measurement of the battery's no-load voltage or open circuit voltage (OCV), when current is flowing, is crucial. OCV is an important metric as it indicates the battery's state of charge. It assists in guaranteeing that the battery was correctly charged during production.
2. Track the no-load voltage of every battery pack cell and determine the average voltage.
It is crucial to confirm that the voltage levels of each individual cell in a battery pack are constant. This guarantees that each of them makes an equal contribution to the battery pack's total performance.
The battery pack's no-load voltage is compared to the average voltage of each cell. This comparison is done to check the deviation from the standard voltage value.

3. Following the comparison, the mean deviation is computed. The mean deviation is used to calculate the average of the absolute deviations of the data from the central point.

4. The mean deviation value checked and if it is less than 1 then go to stop means the battery cell voltages are balanced otherwise if the deviation is more than one than monitor voltage of Each Battery cell and compare each voltage to rated voltage.

5. If a particular Cell block discharging more than another block then short circuit current is measured and a sensor will be activated. This will activate the protective relay and shut down the system. If the discharge in cell block is comparable with another block, then go to stop, means voltages in the cells are balanced.
, Claims:We Claim,
Claim 1: Method for Detecting Defective Cells: A method to identify defective battery cells by measuring open-circuit voltage, calculating deviations, and detecting faults based on threshold comparisons.
Claim 2: System for Cell Performance Monitoring: A system with sensors, a processor, and alert mechanisms to monitor, detect, and report defective cells while preventing unsafe charging.
Claim 3: Battery Pack with Fault Detection: A battery pack that isolates defective cells by comparing individual cell voltages to the average and halts charging when faults are detected.
Claim 4: Method for Ensuring Battery Performance: A method to maintain battery health by monitoring cell voltages, calculating deviations, and activating protective measures against faulty cells.
Claim 5: Diagnostic Technique for Battery Health: A diagnostic technique using sensors and algorithms to detect cell faults, alert operators, and implement corrective actions to ensure safety.