In both Internal Combustion Engine Vehicles (ICEVs) and Electric Vehicles (EVs), the refrigerant charge is essential for efficient climate control and energy consumption. An accurate refrigerant charge allows the system to regulate cabin temperature effectively and optimizing energy use. In ICEVs, this prevents the wastage of engine power. In EVs, it preserves battery life by minimizing energy drain by the climate control systems. Undercharging or Overcharging has adverse effects on the Heat Ventilation Air-Conditioning (HVAC) systems and the energy usage associated with it. Undercharging leads to poor cabin cooling which reduces heat absorption by refrigerant whereas overcharging leads to higher energy consumption by compressor, and potential damage to components, which can lead to wear, leaks, and system failures. Hence it is crucial to use optimum refrigerant charge quantity in Mobile Air-Conditioning (MAC) system both in ICEVs and EVs. Previous work on refrigerant charge determination consisted of performing physical tests and experiments to determine the refrigerant charge quantity. This paper explores the application of 1D Computer Aided Engineering (CAE) to determine the optimum refrigerant charge quantity. The paper presents a comprehensive methodology to accurately determine the optimum refrigerant charge quantity in ICEVs and EVs HVAC systems using 1D CAE simulation by employing the plateau method. The first step is model creation wherein, a 1D model of the HVAC system is developed, including all components like the compressor, condenser, TXV and evaporator. Followed by parameterization of operating conditions: ambient temperature, cabin load, and driving conditions are simulated to reflect real-world scenarios. Then optimization, where in key process parameters from the simulation are captured to draw a correlation with the physical test data. Finally, prediction, where the calibrated model is used to predict the optimum charge quantity for another vehicle by replacing the key components and plumbing. By identifying the optimum refrigerant charge quantity based on the simulation results, this study provides valuable insights for optimizing HVAC system performance and reducing energy consumption in both ICEVs and EVs. Additionally, by leveraging the capability of 1D simulation one can predict the optimum refrigerant charge quantity in an HVAC system of ICEVs or EV well before the proto-build.