Abstract: This disclosure relates to a method and system for real time prediction of tire remaining useful life using a tire digital twin. Herein, the digital twin of the tire monitors a plurality of tires while accounting for runtime as well as parking operation of tires. During runtime, tire goes through multiple operational changes, therefore, the system is configured to estimate the operational changes. The estimation is done in the form of index, which is compared with the manufacturers' recommended value. Similarly, while vehicle is parked, tire still goes through changes which play an important role in its overall health, like, long pending wheel rotation can lead to flat spot. Tire inflation can change owing to cool down effect as well as uncontrolled natural leakages. Further, these parameter indexes are clubbed together to calculate the health index of the tire, which is used to estimate the tire's current remaining useful life.

Abstract: Rotary knifes/cutters play an important role in manufacturing of finished products. The rotary cutters tend to lose their cutting material over time. Hence to compensate, pressure applied by cylinder over rotary cutter needs to be changed. But this change in pressure needs to be optimum as too high pressure can lead to loss of material and too low pressure can stop cutting operation. Present application provides methods and systems for real time estimation of pressure change requirements for rotary cutters. The system first determines minimum and maximum usage limit for rotary cutter based on historical rotary cutter usage data and real-time pressure value using first trained model. The system, upon determining that minimum usage limit is reached, determines time for next pressure change based on physical parameters using second trained model. Thereafter, system compares estimated time with estimated maximum usage limit and displays notification to change pressure based on comparison.

Abstract: Performance optimization of power plants is one of the major challenges. Several machine learning based techniques are available which are used for optimization of the power plants. Coal selection and blending is critical to ensuring optimum operation of thermal power plants. The present disclosure provides a system and method for optimum coal selection for the power plant and power plant optimization. The system mainly comprises two components. First, a coal usage advisory module providing coal usage and blending ratio advice to the operators based on the available coal. The optimization is with respect to the entire power plant operation including its components. And second, a performance optimization advisory module provides operation instruction for boiler, SCR, APH and other power plant equipment based on the implemented coal blend in real-time.

Abstract: This disclosure relates to a method and system o real time prediction of tire remaining useful life using a tire digital twin. Herein, the digital twin of the tire monitors a plurality of tires while accounting for runtime as well as parking operation of tires. During runtime, tire goes through multiple operational changes, therefore, the system is configured to estimate the operational changes. The estimation is done in the form of index, which is compared with the manufacturers' recommended value. Similarly, while vehicle is parked, tire still goes through changes which play an important role in its overall health, like, long pending wheel rotation can lead to flat spot. Tire inflation can change owing to cool down effect as well as uncontrolled natural leakages. Further, these parameter indexes are clubbed together to calculate the health index of the tire, which is used to estimate the tire's current remaining useful life.

Abstract: The efficient operation of an electric vehicle depends greatly on proper functioning of a battery pack in the electric vehicle. A system and method for optimizing the operation of the battery pack in an electric vehicle is provided. The system comprises a digital twin for a battery pack in an electric vehicle. The system determines the state of charge, state of health and temperature distribution in the battery pack using various models. This information can be used to predict optimal charge and discharge profiles of the battery pack for given load conditions, as well as remaining useful life of the battery. The digital twin would require inputs such as battery temperatures from the sensors, coolant flow rates, coolant temperature, ambient temperature, load on the vehicle, current and voltages from the pack and battery characteristics from the manufacturer.

Abstract: Performance and lifespan of batteries deteriorate with time due to various factors. Existing systems for battery management use different approaches for the battery management, and also rely on static value of parameters for State of Health (SOH) and Remaining Useful Life (RUL) estimation, thereby failing to consider current condition of the battery. The disclosure herein generally relates to battery management, and, more particularly, to a method and system for online battery management involving real-time estimation of State of Health (SOH) and Remaining Useful Life (RUL) of a battery, based on real-time data collected from the battery. The system determines state of the battery as one of charging, discharging, and rest. Further, corresponding to the determined state, the system determines values of one or more parameters, and processes the determined values with a battery performance model for online determination of the SOH and RUL.

Abstract: Performance and lifespan of batteries deteriorate with time due to various factors. Existing systems for battery management use different approaches for the battery management, and also rely on static value of parameters for State of Health (SOH) and Remaining Useful Life (RUL) estimation, thereby failing to consider current condition of the battery. The disclosure herein generally relates to battery management, and, more particularly, to a method and system for online battery management involving real-time estimation of State of Health (SOH) and Remaining Useful Life (RUL) of a battery, based on real-time data collected from the battery. The system determines state of the battery as one of charging, discharging, and rest. Further, corresponding to the determined state, the system determines values of one or more parameters, and processes the determined values with a battery performance model for online determination of the SOH and RUL.