1 Plant Archives Vol. 20, Supplement 2, 2020 pp. 673-680 e-ISSN:2581-6063 (online), ISSN:0972-5210 STIRRER SPEED CONTROL OF A FLUIDIZED BED DRYER FOR BIOMASS PARTICLES USING PWM TECHNIQUE Russul A. Kadhim*, Ekhlas M. Fayyadh and Sadeq H. Bakhy 1 Mechanical Engineering Department, University of Technology, Iraq *Corresponding Author Email : eng_russul_ak@yahoo.com. Abstract This study an experimental work was carried out to investigate the effects of speed control of a stirrer motor on the drying quality of biomass particles (i.e. wet wheat particles). Pulse width modulation (PWM) control technique was employed at fluidized bed to find out the required drying time at different static bed heights. To meet these objectives, a stirred fluidized bed dryer (SFBD) was used while a conventional fluidized bed was utilized for comparison purposes. The experiments were conducted at the same operational conditions as in the real working environment where the inlet air temperature is 37°C, inlet air velocity is1.45 cm/s, diameter of wheat particle is 2mm, and its moisture content of particles is 12% for each value of static bed heights, which were 9,12, and 15 cm, respectively. SFBD has two levels straight paddle stirrer with two blades on each level. The ratio of stirrer diameter to the diameter of the fluidized column is 0.95. The controller of stirring speed was build based on the relative humidity inside the bed. The voltage and speed of the stirrer motor were represented at different duty cycle. The results showed that the enhancement in the total drying time was increased from 17.87% to 27.39% as the static bed height increases from 9 cm to 15 cm. Keywords: Fluidized bed dryer, stirrer, PWM, biomass. Introduction In many engineering applications, the control at drying process is one of the most effective techniques in maximizing or minimizing the desired objective functions with prevailing constraints Dufour, (2006), and N. Malekjani et al. (2011). In an early study, a model for fluidized-bed tea drying was utilized by Temple et al. (2000) for the development of a control strategy instead of manual control of the drying operation that limited because of the time taken to reach stability. The fluidization requirements and the drying kinetics for this model were established in experimental studies. The model was simulated in MATLAB. A monitor and control processing in a control strategy in data logging was developed by SLOGGER which consists of microprocessor-based satellite units connected into a network by RS485 serial communication wiring. Other found that to improve fluidization for solid materials that have cohesive characteristics which has some restrictions in the conventional fluidized bed. So, agitation is required. Ambrosio and Taranto (2002) used a mechanical anchor shaped stirring paddle on the drying of fine crystalline organic acid particles, which have diameter 80 mm and density 1.443 g/cm 3 . The influences of initial moisture content and temperature of the drying gas at the entrance of the bed were evaluated by the drying kinetics curves. The result showed that the dried particles produced had better fluidity, which could facilitate the continuity of industrial processing, handling, transport and storage. In a continuous paddy drying process, the paddy moister content varies all times. So, the required drying process to paddy is to maximize the drying capacity of paddy dryer at minimum loss in head yield and minimum energy consumption without affecting the rice quality. Atthajariyakul and Leephakpreeda, (2006) proposed a systematic determination of optimal condition for fluidized bed paddy drying and adaptive fuzzy logic control in order to guarantee good quality and consume energy efficiently. The drying air temperature and the percent of recycle air were considered as controlled variables in the drying process. The results showed the effectiveness of the proposed methodology on the rice quality and energy consumption. Later, Liang and Langrish, (2010) investigated controlling the temperature and the humidity in a stirrer fluidized bed, in order to crystallize skim milk powder from spray drying without caking the powders. The results depicted that the samples from the fluidized bed did not adsorb as much water as the original samples, suggesting that the samples from the fluidized bed were more stable than the original samples. On the other hand, Bait et al. (2011) considered three types of agitator, a straight-blade, pitch-blade, and helical ribbon–type agitator to study the effect of the agitator type on the mixing characteristics and drying kinetics of micrometer- sized, cohesive particles at low air velocity. The study was carried out at different parameters, such as inlet air velocity, temperature, agitation speed and feed loading. The controller and indicator of agitation speed and temperature were installed on the control panel attached to the agitated fluidized bed dryer. The results showed the paving way for a more efficient spiral agitator of the helical ribbon type. Due to make a combination between two dynamic models (linear–nonlinear) of dryer plant to solve the drying rate equation, to improve the dryer control of the rotary dryer plant process, Areed et al. (2012) utilized three different modern adaptive control techniques, ( Direct PID controller, Fuzzy logic controller, and Neuro-Fuzzy controller). The results revealed that the Neuro-Fuzzy control is better and more versatile compared with the other controller techniques.