Abstract

The objective of the paper is to develop a model and a conceptual framework for noise behaviour monitoring and mitigating climate change by imposing global environmental taxes and externalities on “Noise Behaviour” through the monarchy of Concordia. The paper has presented the modelling of noise behaviour taxes and tariffs and climate change mitigation in the monarchy of Concordia. The Design of Experiment (DoE) for modelling “Noise Behaviour Taxes” with the statistical method of “Response Surface Methodology and Robust Parameter Design (Taguchi Technique)” has been utilized. The concepts of energy efficiency and societal well-being are presented by defining energy intensities and noise.

Abstract

Integrating a variety of renewable energy and waste heat resources, the district energy bus system (EBS) has become a core infrastructure for realizing building heating and cooling in the context of the current low-carbon energy transition. This paper focused on office buildings in hot summer and cold winter areas of China, and developed parameter sensitivity research based on correlation analysis and regression analysis with selected parameters. The results show that the sensitivities are different among the input and output parameters. In general, based on correlation analysis and regression analysis, surface water temperature, outlet temperature of surface water coils are the variables with the highest correlation degree with the output parameters. In addition, the cooling load has a higher correlation with the output parameters than the heating load. The results of this paper can be used for parameter selection in system optimization to help confirm the priority of parameters and reduce the uncertainty of model input and output parameters.

Abstract

There is a rising need for accurate battery state of health (SOH) diagnosis in electric vehicle maintenance and second-life evaluation. However, existing methods suffer from the transition from cell-level tests to real-world vehicle applications due to the ignorance of incorporating laboratory tests with large-scale, time-varying field data. This paper proposes a framework combining the system-level capacity calculation and cell-level decoupling experiment for battery system capacity diagnosis. A modified regional capacity calculation method for online applications is presented, and the regional capacity of the battery under various temperatures and SOHs is experimentally determined to decouple various working conditions. This work highlights the opportunity to integrate laboratory test data to leverage unlabelled field data for capacity diagnosis while revealing the characteristics of battery capacity under different working conditions.