Temperature-Based Fan Speed Optimization Strategy

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments,research on intelligent fan speed control systems has become particularly important.This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort.Firstly,by analyzing existing fan speed control technologies,their main limitations are identified,such as the inability to achieve smooth speed transitions.To address this issue,a BP-PID speed control algorithm is designed,which dynamically adjusts fan speed based on indoor temperature changes.Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures.Furthermore,the real-time responsiveness of the system is crucial for enhancing user comfort.Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments.Ultimately,this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.

New Technical Trends on Adjustable Speed AC Motor Drives

Adjustable speed AC Motor drives have been used extensively in modern industry and transportation which calls for electrical and mechanical energy conversion with wide output power range applications.Because of its modularity and scalability,the drive system can be extended to many different application areas.More recently,adjustable speed AC motor drive applications are spreading not only in industry applications,but also sky and the marine.In this paper,after summarizing the history of adjustable speed AC motor drives and applications,the main issues of AC drive technologies are reviewed and investigated in the paper.Technical issues of adjustable speed AC motor drives including its standardization are surveyed and analyzed for more advancement.Finally,the paper provides the latest technical trends on adjustable speed AC motor drives technologies,and discusses the development of high speed high power PM motor.

Machine Learning-Based Approach to Liner Shipping Schedule Design

This paper studied a tactical liner shipping schedule design issue under sail and port time uncertainties,which is the determination of the planned arrival time at each port call as well as the punctuality rate and number of assigned ship on the route.A number of studies have tried to introduce the operational speed adjustment measure into this tactical schedule design issue,to alleviate the discrepancies between designed schedule and maritime practice.On the one hand,weather conditions can lead to speed loss phenomenon of ships,which may result in the failure of ships’punctual arrivals.On the other hand,improving the ability of speed adjustment can decrease the late-arrival compensation,but increase the fuel consumption cost.Then,we formulated a machine learning-based liner shipping schedule design model aiming at above-mentioned two limitations on speed adjustment measure.And a machine learning-based approach has been designed,where the speed adjustment simulation,the neural network training and the reinforcement learning were included.Numerical experiments were conducted to validate our results and derive managerial insights,and then the applicability of machine learning method in shipping optimization issue has been confirmed.