Chengliang Fan
- Development of near-optimal advanced control sequences for chiller plants with water-side economizers in U.S. Climates (ASHRAE RP-1661). Dans: Science and Technology for the Built Environment. :
- An AI-driven electromagnetic-triboelectric self-powered and vibration-sensing system for smart transportation. Dans: Engineering Structures, v. 323 (janvier 2025). (2025):
- Variable damping energy regenerative damper for self-powered sensors and self-sensing devices in smart electric buses. Dans: Smart Materials and Structures, v. 33, n. 10 (18 septembre 2024). (2024):
- (2024): Quantifying the Influence of Different Block Types on the Urban Heat Risk in High-Density Cities. Dans: Buildings, v. 14, n. 7 (2 juillet 2024).
- Impact of urbanization on heavy metals in outdoor air and risk assessment: A case study in severe cold regions. Dans: Sustainable Cities and Society, v. 114 (novembre 2024). (2024):
- Evaluation of energy performance and ecological benefit of free-cooling system for data centers in worldwide climates. Dans: Sustainable Cities and Society, v. 108 (août 2024). (2024):
- A dual-kinetic energy harvester operating on the track and wheel of rail deceleration system for self-powered sensors. Dans: Smart Materials and Structures, v. 32, n. 12 (27 octobre 2023). (2023):
- A novel machine learning-based model predictive control framework for improving the energy efficiency of air-conditioning systems. Dans: Energy and Buildings, v. 294 (septembre 2023). (2023):
- Model-based predictive control optimization of chiller plants with water-side economizer system. Dans: Energy and Buildings, v. 278 (janvier 2023). (2023):
- An online physical-based multiple linear regression model for building’s hourly cooling load prediction. Dans: Energy and Buildings, v. 254 (janvier 2022). (2022):
- Analysis of hourly cooling load prediction accuracy with data-mining approaches on different training time scales. Dans: Sustainable Cities and Society, v. 51 (novembre 2019). (2019):
- Improving cooling load prediction reliability for HVAC system using Monte-Carlo simulation to deal with uncertainties in input variables. Dans: Energy and Buildings, v. 226 (novembre 2020). (2020):
- Cooling load prediction and optimal operation of HVAC systems using a multiple nonlinear regression model. Dans: Energy and Buildings, v. 197 (août 2019). (2019):