• Energy Research
• CN close
• NL close
• EG close

Currently active suspension system is more applicable than passive for improving the suspension performance, ensuring the stability and passenger safety in modern automotive suspension system. However, high energy consumption is one of the main disadvantages of implementing this system in real applications. In this paper, the energy consumption of electromagnetic actuators used for an active suspension system controlled by proportional-integral-derivative (PID), fuzzy adaptive PID, and neuron adaptive PID are investigated through simulation studies. Based on the energy consumption and the performance analysis, it has found that it is potential to develop a vibration energy recovery system to achieve the energy balance requirement in active suspension systems.

Pool boiling in porous media has been applied in various thermal management systems by using latent heat and increasing the heat transfer area and thermal conduction path to improve the heat transfer performance. In mechanical equipment, vibration is an inevitable problem due to reasons such as engine operation and high-speed relative motion between transmission system components, which causes the system components to be affected by vibration forces or vibration accelerations. This study focuses on a review of published articles about the effects of mechanical vibration on the characteristics of boiling process in porous media by two aspects: heat transfer performance and bubble dynamics. Heat transfer coefficient (HTC) and critical heat flux are two main parameters used to measure the boiling heat transfer characteristics of porous media. For bubble dynamics investigations, properties such as migration, fragment, coalescence, departure diameter and frequency are the focus of research attention. Different mechanical vibration parameters, i.e., direction, frequency, and amplitude, will have different effects on the above characteristics. It is worth mentioning that the greatest influence occurs under resonance conditions, and this has been verified through experimental and simulation calculations. This review highlights the importance of considering mechanical vibrations in the design and optimization of porous media systems for efficient heat transfer applications. Further research is warranted to explore the detailed mechanisms and optimize the vibration parameters for enhanced heat transfer performance in thermal management systems using porous media.

Environment-friendly treatment of sewage sludge has become tremendously important. Conversion of sewage sludge into energy products by environment-friendly conversion process, with its energy recovery and environmental benefits, is being paid significant attention. Direct liquefaction of sewage sludge into bio-oils with supercritical water (SCW) was therefore put forward in this study, as de-water usually requiring intensive energy input is not necessary in this direct liquefaction. Supercritical water may act as a strong solvent and also a reactant, as well as catalyst promoting reaction process. Experiments were carried out in a self designed high-pressure reaction system with varying operating conditions. Through orthogonal experiments, it was found that temperature and residence time dominated on bio-oil yield compared with other operating parameters. Temperature from 350 to 500°C and reaction residence time of 0, 30, 60min were accordingly investigated in details, respectively. Under supercritical conversion, the maximum bio-oil yield could achieve 39.73%, which was performed at 375°C and 0min reaction residence time. Meanwhile, function of supercritical water was concluded. Fuel property analysis showed the potential of bio-oil application as crude fuel.

Abstract This study investigates the non-linear relationship between urbanization paths and CO2 emissions in selected South, South-East, and East Asian countries over the period 1971–2014. Based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework, we applied the advanced and robust methods of dynamic seemingly unrelated regression (DSUR), dynamic OLS (DOLS), and fully modified OLS (FMOLS) to estimate the long-term effects. The empirical findings revealed the inverted U-shaped effects of urbanization and urban agglomeration and the U-shaped impact of the largest city ratio on CO2 emissions. Urbanization and urban agglomerations improve environmental quality in the long-run and support ecological modernization theory. However, excessive concentration in the largest cities have severely affected the environmental quality and violates the notion of compact-city efficiencies. Moreover, energy intensity and economic growth positively affect CO2 emissions, while trade openness negatively influences CO2 emissions. Our robustness analysis at the country-level applies the augmented mean group (AMG) panel ARDL technique, which further supports the non-linear effect of urbanization paths on CO2 emissions except for a few countries. The results of the panel Granger non-causality approach unveil bidirectional causality of energy efficiency, economic growth, urbanization, and largest city ratio with CO2 emissions. In contrast, unidirectional causality runs from urban agglomeration to CO2 emissions. Our findings have important policy implications as we suggest green urban infrastructures, eco-friendly dwellings, smart cities, country-specific trade policies, and renewable energy options to improve the environmental quality.

Improving efficiency, reducing expenses, and ensuring sustainability in today’s competitive market is made possible by optimising the performance of the food supply chain (FSC). A strong decision-making framework is required to overcome obstacles including high transportation and production costs, uneven quality, and the impact on the environment. To solve these problems, this paper presents an all-inclusive multi-criteria decision making (MCDM) framework that uses enhanced relative utility and nonlinear standardisation (ERUNS) to rank alternatives, Logarithmic percentage change-driven objective weighing (LOPCOW) to determine objective weights, and subjective weight assignment by ratio analysis (SWARA) to determine subjective criterion weights. LOPCOW offers objective weights grounded in facts and indifference thresholds, whereas SWARA records decision-makers (DMs) preferences in weighing factors like sustainability and cost efficiency. The ERUNS methodology then uses utility degree assessments and matrix standardization to rank and evaluate alternatives. An improved method of assessment is to make use of intuitionistic fuzzy sets (IFS), which deal with ambiguity by adding membership, non-membership, and hesitation levels. By merging subjective and objective data, this integrated method maximizes FSC performance, provides useful insights for enhancing overall efficiency and sustainability, and offers a viable answer to contemporary difficulties. It also offers helpful insights for improving overall efficiency and sustainability, and it provides a practical response to the challenges that are now being faced.

Abstract A great deal of heat is wasted in intensive public shower facilities, such as those in schools, barracks and natatoriums, which open up at specified time. It will contribute a lot to energy saving and environmental protection with significant economic benefits to recycle the exhaust heat. In this paper, we propose two different kinds of heat pumps (an electric heat pump and an absorption heat pump) in the heat recovery systems. In both system, the used shower water is drained through a pipe and collected in a gray water pool. When the wastewater reaches certain volume, the heat pump system will begin working and recycling heat. The wastewater is filtered and piped to the heat exchanger to exchange heat with the tap water whose temperature will increase from 12 °C to 25 °C with the wastewater temperature dropping from 30 °C to 17 °C. Then the wastewater is piped to the heat pump evaporator and the tap water is piped to the condenser for farther heating. According to the different characteristics of the electric heat pump and absorption heat pump, we also introduce the processes and control methods of different heat recovery systems in details in this paper. Based on a practical example, this paper analyzes and compares the economic and environmental benefits of three retrofitting schemes, including “exhaust heat recovery using electric heat pump”, “exhaust heat recovery using electric heat pump + gas boiler” and “exhaust heat recovery using direct-fired heat pump”. Then we find out that the heat recovery system using direct-fired absorption heat pump has lower energy consumption, less pollution, lower operating cost, and shorter payback period. And it has a promising practical application.

The battery power state (SOP) is the basic indicator for the Battery management system (BMS) of the battery energy storage system (BESS) to formulate control strategies. Although there have been many studies on state estimation of lithium-ion batteries (LIBs), aging and temperature variation are seldom considered in peak power prediction during the whole life of the battery. To fill this gap, this paper aims to propose an adaptive peak power prediction method for power lithium-ion batteries considering temperature and aging is proposed. First, the Thevenin equivalent circuit model is used to jointly estimate the state of charge (SOC) and SOP of the lithium-ion power battery, and the variable forgetting factor recursive least squares (VFF-RLS) algorithm and extended Kalman filter (EKF) are utilized to identify the battery parameters online. Then, multiple constraint parameters including current, voltage, and SOC were derived, considering the dependence of the polarization resistance of the battery on the battery current. Finally, the verification experiment was carried out with LiFePO4 battery. The experimental results under FUDS operating conditions show that the maximum SOC estimation error is 1.94%. And the power prediction errors at 20%, 50%, and 70% SOC were 5.0%, 8.1% and 4.5%, respectively. Our further work will focus on the joint estimation of battery state to further improve the accuracy.