Characterization of Semiconductor Detectors by DLTS by Prof. Dr. Muhammad Asgahr Hashmi The Islamia University of Bahawalpur

Outline  pn junctions as radiation and particle detectors ■ Radiation-induced defects in semiconductors ■ The interaction of electron traps with electrons ■ Characterization of traps with DLTS ■ Worth to know about DLTS

Part-II Dual Axis Solar Tracking System

Arrangement of the Proposed Solar Tracking System

Fuzzy logic based solar tracking system are designed and implemented to track sunlight with higher degree of accuracy by pointing the solar panel always towards the sun in most of the day time.

Fuzzy Logic Basics Fuzzy logic addresses such applications perfectly as it resembles human decision making with an ability to generate precise solutions from certain or approximate information. Facial pattern recognition Transmission systems Unmanned drone/helicopter Smart households like washing machines etc.

Block Diagram of Fuzzy Logic Based Solar Tracking System

Plot of M.F’s for O/P Variable, SM-2 “Vertical Motor Control” Plot of M.F’s for O/P Variable, SM-1 “Horizontal Motor Control”

Ranges and M.F.’s Membership Function (MF) Ranges (Voltage)Region Occupied Most Left-6 to -41 More Left-6 to Little Left-4 to 02-3 Balanced-2 to 23-4 Little Right0 to 44-5 More Right2 to 65-6 Most Right4 to 66

Complete Set of Rules for Solar Tracking System

A Situation - Example Input Variables Input Voltage (u) Values Region Selection Fuzzy Set Calculation Horizontal Position C H 1.25 x=2u=2.5 2≤x<4 Region-5 f 1 =( )/2=0.75 f 2 =1-f 1 =1-0.75=0.25 Vertical Position C V 2.4 x=2u=4.8 4≤x<6 Region-6 f 3 = ( )/2=0.6 f 4 = 1-f 3 =1-0.6=0.4 The symbol ^ presents the operation of “min-AND” b/w the corresponding values of M.F’s.

Rules Horizontal position C H Vertical position C V Horizontal Motor Control SM-1 Rotation( o ) Vertical Motor Control SM-2 Rotation ( o ) 1. Little rightMore downLittle C.W = 0.66More C.W= 0.83S1S1 1. Little right Most down Little C.W = 0.66Most C.W= 1.0S2S2 1. More rightMore downMore C.W = 0.83 S3S3 1. More right Most down More C.W = 0.83Most C.W = 1.0S4S4

iRiRi SiSi R i * S i ΣS i *R i =1.075; ΣS i *R i ∕ ΣR i = 1.075/1.5= = 71.6% for SM-1 motor in the clock wise rotation. iRiRi SiSi R i * S i ΣS i *R i =1.3555; ΣS i *R i ∕ ΣR i =1.3555/1.5= = % for SM-2 motor in the clockwise direction.

Fuzzy logic controller Four Input current values from the four “Light Dependent Resistors” installed on solar panel Two output values as the “Stepper Motor Speeds” for the alignment of the solar panel

MATLAB (Simulink) Results Overview

Specifications of the PV panel used Model No.TBP-1235 ISC2.25 A V OC 21.2 V I MP 2.06 A V MP 17V P MIN 35W N S (No. of cells)36 Nominal irradiance at 25°C1000

Output power with/without tracker Time of the day PV panel output values without trackerPV panel output values with tracker V(V)I (A)P(W)V(V)I(A)P(W) 7:00 am :00 am :00 am :00 am :00 am :30 am :00 pm :00 pm :00 pm :00 pm :00 pm :00 pm :00 pm :00 pm Total

Efficiency of the system WITHOUT solar tracking system

Efficiency of the system WITH solar tracking system

Conclusion The completed simulation of FIS (Fuzzy Inference System) in MATLAB is also verified in SIMULINK environment. The efficiency of the solar panel increases reasonably by the use of dual axis solar tracking system. The results confirm reliability of the system. The system is easily expandable to control several PV panels at the same time.

Thank You.