This study analyzes the characteristics of alumina (Al2O3)/water nanofluid to determine the feasibility of its application in an air-cooled heat exchanger for heat dissipation for PEMFC or electronic chip cooling. The experimental sample was Al2O3/water nanofluid produced by the direct synthesis method at three different concentrations (0.5, 1.0, and 1.5 wt.%). The experiments in this study measured the thermal conductivity and viscosity of nanofluid with weight fractions and sample temperatures (20-60°C), and then used the nanofluid in an actual air-cooled heat exchanger to assess its heat exchange capacity and pressure drop under laminar flow. Experimental results show that the nanofluid has a higher heat exchange capacity than water, and a higher concentration of nanoparticles provides an even better ratio of the heat exchange. The maximum enhanced ratio of heat exchange and pressure drop for all the experimental parameters in this study was about 39% and 5.6%, respectively. In addition to nanoparticle concentration, the temperature and mass flow rates of the working fluid can affect the enhanced ratio of heat exchange and pressure drop of nanofluid. The cross-section aspect ratio of tube in the heat exchanger is another important factor to be taken into consideration.

As carriers of green energy, proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells are complex and nonlinear multivariate systems. For simulation analysis, optimization control, efficacy prediction, and fault diagnosis, it is crucial to rapidly and accurately establish reliability modules and extract parameters from the system modules. This study employed three types of particle swarm optimization (PSO) algorithms to find the optimal parameters of two energy models by minimizing the sum squared errors (SSE) and roots mean squared errors (RMSE). The three algorithms are inertia weight PSO, constriction PSO, and momentum PSO. The obtained calculation results of these three algorithms were compared with those obtained using algorithms from other relevant studies. This study revealed that the use of momentum PSO enables rapid convergence (under 30 convergence times) and the most accurate modeling and yields the most stable parameter extraction (SSE of PEMFC is 2.0656, RMSE of PV cells is 8.839 · 10⁻⁴). In summary, momentum PSO is the algorithm that is most suitable for system parameter identification with multiple dimensions and complex modules.

A thermal management system using alumina (Al₂O₃)/water as the nanofluid for green power sources was experimentally assessed in this paper. Basic thermal principles and formulas were utilized to evaluate the performance of an air‐cooled heat exchanger. The Al₂O₃/water nanofluid was produced at the concentrations of 0.5, 1.0, and 1.5 wt.%. The testing conditions of this experiments were above three concentrations, five coolant flow rates (0.8, 1.2, 1.6, 2.0, and 2.4 L/min.), and three heating powers (50, 100, and 150 W). Firstly, basic properties of nanoparticles were analyzed. Fundamental relationships of the Al₂O₃/water nanofluid with respect to temperatures and concentrations were measured such as: viscosity, density, and specific heat. Next, an innovative concept named efficiency factor (EF) was proposed to quantitatively evaluate the thermal system performance. The enhancement of thermal system performance compared with distilled water was then defined as an efficiency factor ratio (R_EF). The experimental results demonstrated that the efficiency factor ratios were optimal at low flow rate (0.8 L/min.) and low concentration (0.5%). Values of R_EF were all below 1.0 at high flow rates (1.2–2.4 L/min.). This research points out the direction of optimizing a thermal management system for green energy sources in the near future.

This study was conducted to characterize carbon nanotube (CNT)/water nanofluids (CNWNFs) and to apply the nanofluids in a heat‐dissipation system of dual green energy sources. CNTs were mixed with water in weight fractions of 0.125%, 0.25%, and 0.5% to produce nanofluids. The thermal conductivity, density, viscosity, and specific heat of the nanofluids were measured. An experimental platform consisting of a simulated dual energy source and a microchip controller was established to evaluate the heat‐dissipation performance. Two indices, the heat dissipation enhancement ratio and specific heat dissipation enhancement ratio (SHDER), were defined and calculated. The CNWNFs with a CNT concentration of 0.125 wt.% were used because they exhibited the highest SHDER. The steady‐state performance was evaluated at 2 flow rates, 11 hybrid flow ratios, and 3 heating ratios for a total power of 1000 W. The transient behavior of the energy sources at preset optimal temperatures was examined, and the CNWNFs exhibited average increases in stability and heat dissipation efficiency of 36.2% and 5%, respectively, compared with water. This nanofluid heat‐dissipation system is expected to be integrated with real dual energy sources in the near future.

The performance assessment and vehicle verification of nano-alumina (Al₂O₃) engine oil (NAEO) were conducted in this study. The NAEO was produced by mixing Al₂O₃ nanoparticles with engine oil using a two-step synthesis method. The weight fractions of the Al₂O₃ nanoparticles in the four test samples were 0 (base oil), 0.5, 1.5, and 2.5 wt. %. The measurement of basic properties included: (1) density; (2) viscosity at various sample temperatures (20–80 °C). A rotary tribology testing machine with a pin-on-disk apparatus was used for the wear test. The measurement of the before-and-after difference of specimen (disk) weight (wear test) indicates that the NAEO with 1.5 wt. % Al₂O₃ nanoparticles (1.5 wt. % NAEO) was the chosen candidate for further study. For the scooter verification on an auto-pilot dynamometer, there were three tests, including: (1) the European Driving Cycle (ECE40) driving cycle; (2) constant speed (50 km/h); and (3) constant throttle positions (20%, 40%, 60%, and 90%). For the ECE40 driving cycle and the constant speed tests, the fuel consumption was decreased on average by 2.75%, while it was decreased by 3.57% for the constant throttle case. The experimental results prove that the engine oil with added Al₂O₃ nanoparticles significantly decreased the fuel consumption. In the future, experiments with property tests of other nano-engine oils and a performance assessment of the nano-engine-fuel will be conducted.