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In order to correctly read the measuring signals from sensors, each sensor needs to be configured in Simulink by assigning the correct input and output type to it, such as analog digital converter (ADC) type, digital analog converter (DAC), time processor unit (TPU). Fig. A.5 shows the I/O channels and pins connected. Table A.3 shows the wires and PIN connections to the sensors and actuators.

Figure A.5: MicroAutoBox I/O channels connected.

Sensors have to be calibrated before they can measure correctly. Some sensors have been previously calibrated by their manufacturers and the calibration information is avail- able, so they do not need to be calibrated again. However, some sensors do not supplied with calibration information, so they need to be calibrated before use. The sensors require calibrations in this work include temperature sensor and pressure sensor, and the calibra- tion methods have been described below. Calibration information is available for all the other sensors used in this work.

Temperature sensor used is thermocouple type. A thermocouple (see Fig. A.6) is a temperature-measuring device consisting of two dissimilar conductors that contact each

Table A.3: MicroAutoBox PIN connections

Wire colour pattern Sensors connected to PIN position PIN type

orange(o) EGR feedback W1 ADC con1 ch4 in

green(g) encoder speed (B) M2 CTM ch1

violet(v) temperature b2 ADC con3 ch1 in

pink(p) Smoke+ V1 ADC con2 ch4 in

yellow-r Smoke- Z1 ADC con2 ch2 in

g-brown EGR drive D2 DAC 2 out

yellow-blu pressure 2+ a1 ADC con1 ch2 in

r-brown pressure 1+ c1 ADC con1 ch1 in

r-black VGT feedback b1 ADC con2 ch1 in

r-blu VGT Drive D1 DAC 1 out

white-blu flow meter+ Y1 ADC con1 ch3 in

white-r flow meter- X1 ADC con2 ch3 in

grey accer pedal position M5 CTM ch3

white EGR meter Z2 ADC con3 ch2

other at one or more spots. It produces a voltage when the temperature of one of the spots differs from the reference temperature at other parts of the circuit. This change of voltage produced is proportional to the temperature changes. To calibrate a thermal couple, two reference temperature are required. For example, 100℃ (boiling water) and 0℃ (ice and water mixture). Record the voltage at 100℃ and 0℃ respectively and make a look-up table with these two points (see Fig. A.7).

Voltage difference to be

measured +-

Probe, merge into the object to be measured

(a)

Temperature (liquid, gas) to be measured

(b)

Figure A.6: Illustration of a thermal couple. (a) a real photo, (b) measuring principle of thermal couple.

Figure A.7: Thermal couple configuration and calibration model created in Simulink Pressure sensor used is Gems 2200 series, they are molecularity bonded high output strain gauges to provide 100mV output for full range pressure when used with a 10V d.c. power supply [63]. The change of voltage output is proportional to the change of pressure. To calibrate these pressure sensors, a pressure generator is needed. Connect a pressure sensor to the pressure generator, record two voltage readings at two different pressures generated by the pressure generator, and then make a look up table in Simulink (see Fig A.9).

Because the voltage output variations from a thermal couple and a pressure sensor are comparatively small compared to the 0 -5V voltage input range of the Analog input channel, so the temperature and pressure reading would not be accurate enough if directly connect the sensor to MicroAutoBox. A electric signal amplifier card (see Fig. A.10) is used to amplify the voltage variation range of these sensors to match the range of the MicroAutoBox analog input range 0 - 5V.

(a)

(b)

Figure A.8: Gems 2200 series pressure transducer. (a) photos of pressure transducers, (b) illustration of the measuring circuit. [34]

5V power supply

Connected to thermal couple voltage output

Connected to pressure sensors voltage output

inlet

pressure _pressureexhaust

Amplified voltage signal for pressure sensors

inlet pressure

exhaust pressure

Amplified voltage signal for temperature sensor

8 Variable resistors which used to adjust the amplify

ratio

Figure A.10: Amplifier card used for thermal couple and pressure sensors.

A.11). Incremental encoders are sensors capable of generating signals in response to rotary movement. The shaft encoder generates a signal for each incremental change in position. Fig. A.12 shows the Simulink model created.

Figure A.11: Hengstler rotary incremental shaft encoder (RI32-0/360ER.14KB) [37].

Figure A.12: Shaft encoder configuration and calibration model created in Simulink The intake fresh air flow was measured using a Labcell Meriam laminar flow element

(see Fig. A.13) which measures the volume flow rate of gas based on capillary flow prin- ciples. In order to obtain the mass air flow, a formula governed by the ideal gas law was used to translate the volume flow rate to mass flow rate. According to the manual [49], the measurement has an accuracy of ±0.72 LPM of reading. The configuration and calibration model created in Simulink is shown in Fig. A.14.

(a)

(b) [49]

Figure A.13: Labcell Meriam laminar flow meter for measuring the intake air flow.

The EGR gas flow was measured using an ABB OriMaster FPD500 orifice flow meter (Fig. A.15 a). This flow meter measures the volume flow rate based on the orifice fluid measuring principle (Fig. A.15 b). The principle is that the fluid flow rate is a function of the pressure difference across the restriction. This flow meter has a built-in transferring module which takes gas temperature into account, therefore the output from this meter is directly mass flow rate. According to the specifications of the flow meter [1], the system accuracy of a calibrated meter at reference conditions (for Re>105_{) is ±1% of flow rate} with a repeatability of 0.1%. The configuration and calibration model created in Simulink is shown in Fig. A.16.

(a)

(b)

Figure A.15: ABB OriMaster FPD500 compact orifice flow meter. (a) Flow meter body, (b) Orifice measuring principle. [1]

Figure A.16: EGR flow meter configuration and calibration model created in Simulink. The oxygen level in the exhaust manifold was measured by an ECM OXY6200 oxygen sensor. With a input power range from 11VDC to 28VDC, the output analog signal is from 1.0V to 5.5V which is linearized in oxygen percentage 0.0% to 25.0% [30]. The configuration and calibration model created in Simulink is shown in Fig. A.18.

Pedal position sensor uses a PWM signal ranges from 0 to 100%. The configuration model created in Simulink is shown in Fig. A.19.

Figure A.17: OXY6200 oxygen sensor used for measuring the exhaust manifold oxygen level [30].

Figure A.18: Oxygen sensors configuration and calibration model created in Simulink.

Soot was measured using an AVL 439 opacimeter. The measurement principle, the zero-level stability and the signal rise time can be found in Fig. A.20 [9]. The figure shows that the zero-level stability is within 0.2% in terms of opacity of the gas and the rise time from 10% to 90% is 100 ms. The configuration and calibration model created in Simulink is shown in Fig. A.21.

(a)

(b) _(c)

Figure A.20: AVL 439 opacimeter. (a) Measurement principle, (b) Zero-level stability, and (c) Signal rise time.

NOx was measured by a Testo 350 emission analyser. The measurement range and the rise time information are listed in Table A.4.

Figure A.21: AVL 439 opacimeter configuration model created in Simulink. Table A.4: Testo 350 emission analyser

Gases Measurement range Resolution Accuracy Response time

NO 0 - 4000ppm 1ppm ±5% of reading (100 - 1999ppm) <30s (t90)

NO2 0 - 500ppm 0.1ppm ±5% of reading (100 - 500ppm) <40s (t90)