The rising demand for energy-efficient HVAC systems has positioned chillers as critical components in sustainable cooling strategies, particularly in large-scale commercial and industrial applications. However, chillers are also among the most energy-consuming units, necessitating urgent optimization efforts. This research investigates the performance enhancement of chiller systems through the integration of electronic control technologies within a tiered, multi-stage cooling framework. The study adopts a qualitative literature review methodology, synthesizing peer-reviewed findings from 2019–2025 to analyze advancements in programmable logic controllers (PLC), adaptive load-based algorithms, and smart sensor systems in optimizing chiller operations. The results highlight that electronic control systems enable real-time monitoring and dynamic adjustments in chiller performance parameters, significantly reducing energy consumption and operational inefficiencies. Implementations involving PLCs, fuzzy logic, and AI-based controllers have demonstrated energy savings ranging from 15% to 21%, while also contributing to CO₂ emission reductions and enhanced equipment longevity. Furthermore, simulation and real-world applications reveal that adaptive control models are capable of maintaining temperature stability, reducing mechanical stress, and ensuring system reliability across variable thermal loads. Integration with MATLAB/Simulink further validates the scalability and precision of these control strategies. This study concludes that smart control systems embedded in tiered chiller setups offer a robust pathway toward environmentally friendly and cost-effective HVAC solutions. The findings support future adoption in sustainable building designs and industrial cooling applications.
Karjadi et al. (Mon,) studied this question.