Micro Hybrid Systems are a premier approach for improving fuel efficiency and reducing emissions, by improving the efficiency of electrical energy generation, storage, distribution and consumption, yet with lower costs associated with development and implementation. However, significant efforts are required while implementing micro hybrid systems, arising out of components like Intelligent Battery Sensor (IBS).IBS provides battery measurements and battery status, and in addition mission critical diagnostic data on a communication line to micro hybrid controller. However, this set of data from IBS is not available instantly after its initialization, as it enters into a lengthy learning phase, where it learns the battery parameters, before it gives the required data on the communication line. This learning period spans from 3 to 8 hours, until the IBS is fully functional and is capable of supporting the system functionalities. This scenario poses a great challenge to conduct the system performance checks at End of Line testing stations in assembly lines, and also in after sales service stations, as the battery data is not available, without which the micro hybrid systems cannot perform their full set of functions.This paper discusses a novel approach to solve this problem by implementing a master-slave approach for the Battery Management System, which enables the systems engineer to override the IBS data, and devise the methods to perform full functionality checks on the micro hybrid system, while IBS is still in learning phase, and is not capable of supporting the functions of micro hybrid systems.