Washing machines (WMs) are common household appliances that help to save time and effort used in brushing and washing clothes. It is a common practice to use manually operated WMs, and based on their uses, WMs are classified into top and front open cloth washing machines, which operate based on an automatic control mechanism. In this paper, we present the design and simulation of an Arduino fuzzy logic-based WM control system, with an emphasis on improvement in its operating algorithm. Simulations were performed to determine the optimal time the WM takes to wash clothes, the maximum number of clothes the WM can wash per time, the acceptable dirtiness level of cloths, and the type of clothes that the machine can wash. The number of clothes to be washed, the degree of dirtiness, and the type of clothes govern the fuzzy logic control process adopted by the WM. The output voltage of the WM varies as the degree of dirtiness of the water varies from 0 to 1.95 V for very dirty water output from washed clothes and varies from 4 to 4.89 V for low-contaminated water. Another constraint considered was the load current, which increased as the number of clothes increased. The WM’s operation time is determined by the amount of voltage and load current used during its operation. As a result, the control of the WM is dependent on the dirtiness level of the clothes and the amount of load.

Towards the Optimal Performance of Washing Machines Using Fuzzy Logic

One of the key features of washing an automated machines is the noise and vibration it produces, or more technically, the decibel level it produces. Numerous of home appliance companies have put in much effort to solve this problem but there is still large room for further improvements especially in the rinse and the spin cycles of the washing machine. This work illustrates the performances of a multi-body modelled of washing machines realized with the aim to analyze the vibrational acoustic emission. An experimental measurement has been carried out using a digital sound level meter (SLM) to determine the overall noise produced by four different models of automated washing machines with a view of noting the model that has the highest sound pressure level during the three different cycles (the wash, rinse and spin). Result shows that all the machines produced their highest noise during the spinning cycle. Out of the four different model considered. IPSO HF: 304 has the highest sound level of 99.62dB during its spin cycle when maximum load of 30Kg was applied, followed by Imesa RC 23 with a 96.13dB. On the other hands, LG: Direct Drive 13 has the least sound pressure level of 84.75dB. With this knowledge in mind, one can advise a buyer which model to purchase from the market and if an operator must use the machine, how long he can operate such machine without health challenges.

Performance Analysis of Multi-Body Modeled Washing Machines (MBomWM)

A thorough experimental investigation was carried out to diurnally analyze the performance of photovoltaic systems deployed for domestic purposes under the guinea savannah atmosphere in Ogoja, Cross River State, Nigeria. In this study, the time of day to expect maximum efficiency from the photovoltaic (PV) module is shown, and the time of day that the panel temperature will exceed it maximum operating cell temperature is also shown. Instruments employed in the process include a digital solar power meter, digital hygrometer, digital infrared gun thermometer and a digital high precision photovoltaic panel maximum power point tracker (MPPT) to track and determine the maximum power, voltage and current produced by the photovoltaic module. The result shows that the highest level of efficiency was attained at 14:30 which reveals that the climatic condition which occurs at 14:30 is the most favorable for PV systems deployed for domestic purposes at the location. The study shows that 42% and 400C is the best relative humidity and PV temperature level for optimum PV efficiency at this location. In addition, the temperature of the study location appears encouraging as on average, the panel temperature will rarely exceed the maximum operating cell temperature for months besides January and march in which a cooling mechanism to regulate the panel temperature may be needed to avoid a massive loss in efficiency. An altitude of 85m above sea level makes the location relatively favorable for receiving intense solar radiation. With 90% efficiency assured, the location can be seen as suitable for generating electricity via PV technology and installing solar farms for commercial purposes.

Effiong A. Archibong

Papers

Performance Analysis of Multi-Body Modeled Washing Machines (MBomWM)

Diurnal Analysis of the Performance of Photovoltaic Systems under the Guinea Savannah Atmosphere in Ogoja, Cross Rivers State, Nigeria