AN3914, Modern Altimeter and Barometer System using ... - Freescale

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Table 3. Pressure and Temperature World-Wide at that Altitude Altitude (m) Altitude (ft) Pressure (mmHg) Pressure (kPa) Temp Avg (°C) 0 0 706 94.13 15 305 1000 732.9 97.7 13 610 2000 706.6 94.2 11 914 3000 681.1 90.81 9.1 1220 4000 656.3 87.5 7.1 2133 7000 586.4 78.18 1.1 2743 9000 543.2 72.42 -2.8 3353 11000 502.6 67.01 -6.8 4572 15000 428.8 57.17 -14.7 6096 20000 349.9 46.65 -24.6 Note: For large range measurements, temperature shifts become important as the temperature compensation of the MPL115A sensor comes into a dramatic role. Although the altitude is not going to be linear with pressure over the 50 to 115 kPa range, it can be assumed to be linear for very small sections. i.e. from a given location to 10 m in higher or lower elevation, the pressure can be assumed linear. Notice too that the pressure can be better resolved in ADC counts at lower altitude than at higher ones. For example pressure at 50 kPa vs. 101 kPa (sea level): 50 kPa = 5642.17 m; 51 kPa = 5483.92 m. The difference is 158.25 m for the 1 kPa change in pressure. At 101 kPa the altitude is 23.7 m. 102 kPa is -55.03 m (below sea level). This is 78.73 m for the 1 kPa change in pressure. Given that the ADC counts are about 15 to 16 counts for each kPa there is better resolution of 5.24 meters/count for the sea level (101 to 102 kPa) than at high elevation 10.55 m/count (50 to 51 kPa). Sea level and below will yield the best altitude to ADC count relationship, as it measures the smallest distance with the most amount of ADC counts. This is because the air is most dense in this region. It also makes the part more useful as the most populated regions do not reside in the 50 kpa area, but between sea level and 81 kPa. A reference table has been included in the appendix for cities and their altitudes. Overview The host microcontroller does the main calculations to determine the Pressure compensated for Temperature variations. MPL115A contains coefficients that are used via a second order compensation algorithm to determine the Pcomp (Compensated Pressure). The coefficients are read to the host microcontroller via I 2 C or SPI in memory address locations where they are stored. The host microcontroller also reads raw Pressure and Temperature data directly from MPL115A. With the combination of the coefficients, Raw Temperature and Pressure, the compensation algorithm is used to calculate Pcomp. The value is a 10 bit number 0 to 1023 which represents 50 to 115 kPa respectively. Note: Simple calculations would lead that (Pressure Range)/(ADC counts) would lead to a resolution of 65 kPa/1023 or 0.064 kPa per an ADC count. However, due to code-skipping this is not necessarily true. The data sheet has a specification of 0.15 kPa Resolution that is more accurate. This is that every 2.36 ADC counts represent a 0.15 kPa pressure change. We guarantee a 1 kPa accuracy across the -40°C to 105°C. While we get better results than this, it is the conservative data sheet spec that is guaranteed. A 0.15 kPa change at sea level is the equivalent of 11.8 m for a 0.15 kPa pressure difference. This is done over 2.36 ADC counts, so it can be ‘pushed’ towards a possible 5 m per ADC count at this level. It will measure the 11.8 m interval more accurately than a 5 m interval. Note that this is not the same for all altitudes. Higher altitudes will have decreased performance, but can be calculated. AN3914 Sensors Freescale Semiconductor 4
Pressure Change Altitude Change (m) ADC Change (counts) (meters/count) 50 kPa to 49.85 kPa -24 2.36 10 70 kPa to 69.85 kPa -17.1 2.36 7.2 90 kPa to 89.85 kPa -13.3 2.36 5.6 101 kPa to 101.15 kPa 11.9 2.36 5 The MPL115A has a specification of a 0.15 kPa Resolution. While searching online for the current barometric pressure, the correct pressure may not be found. Most airports and cities have their current barometric pressure listed for weather conditions. In order to determine weather patterns, the current barometric conditions are often normalized with sea level. This removes altitude variation from the readings. So if the weather is clear, it may be listed as 101.3 kPa, but in actuality it may be 92 kPa. Please keep this in consideration when looking up the local altitude in kPa. WEATHER The MPL115A is an absolute device that can be used to predict and measure the barometric pressure to deduce weather patterns. Weather prediction requires a static location for the sensor and 2-3 hours to analyze a full weather pattern. Typically the pressure changes due to weather are slow, requiring a few hours to determine the sloping of the pressure change. Vertical movement or a significant airflow can interfere with results due to only weather patterns in barometric pressure. The sensor should be kept in a relatively protected area from any strong air flows, and kept at that static location during analysis. Temperature effects can change the results of a normal pressure sensor especially if the measurement is done over several hours in varying temperature. Due to the nature of the calibration and temperature compensation, MPL115A meets these requirements, compensating for temperature swings over a large 0 to 85°C operating range. It will not require auto-zeroing for shifts in offset or span over temperature. How Pressure Increases and Decreases with Weather For weather pattern prediction, the MPL115A is a well suited device with its pressure range and resolution. Barometric pressure changes can directly correlate to changes in the weather. Low pressure is typically seen as the precursor to worsening weather. High pressure increases can be interpreted as improving or clear weather. The typical reasoning can be seen in a comparison of molecular weights. If air is approximately 21% O 2 (g), 78% N 2 (g), O 2 (g) has a molecular mass of 32, N 2 (g) has a mass of 28. H 2 O (g) has a molecular mass of 18. So if there is a large amount of water vapor present in air, this air is going to be lighter than just regular dry air by itself. It’s an interesting fact that explains how weather patterns lead to high or low pressure. If bad weather originates in an area in the formation of water-vapor clouds, this is falling pressure on a barometer. The vapor will reduce the barometric pressure as the H 2 O reduces the mass above that point on the earth. High pressure will signal the clearing of the water vapor as the air dries. Another quandary is how weather during severe hurricanes/cyclones with high 150 mph winds be defined as low pressure? This is due to the fact that hurricanes are low pressure conditions surrounded by higher pressure. The rush of air from higher to low pressure creates the fast moving winds. The lower the pressure in the center, the greater differential pressure between high and low areas. This leads to a stronger cyclone or hurricane. Some areas are harder to predict weather patterns. Cities located at the base of mountainous regions where condensation and fog are a daily occurrence is an example. An area like Hawaii where high colder mountains meet low warm sea regions can have harder to predict results. A network of sensors can give a more exact trend, but for a single sensor in a static location, there are a few ways to have a simple standalone weather station. Local Weather Stations When implementing a weather station, it is best to will check results with a local forecast. When researching local weather pressures, such as barometric pressure at the closest airport, remember that the weather is normalized for altitude. Normalization takes local barometric pressure and shifts it to reflect sea level altitude. Sea Level is 101.3 kPa, and by normalizing various points on a map, a meteorologist can see the weather pattern over a region. Without the normalization, the effect of altitude on the pressure reported by collection points will lead to useless data. A mountain data point will have pressure affected by altitude and as it leads to the valleys, the pressure point there will be higher, telling nothing about the weather without the normalization. AN3914 Sensors Freescale Semiconductor 5
Page 1 and 2: Freescale Semiconductor Application
Page 3: Table 2. Pressure vs. Altitude Pres
Page 7 and 8: Simple Weather Station Code ///////
Page 9 and 10: Algorithm Code for Advanced Weather
Page 11 and 12: Display Code to Output to LCD Scree
Page 13 and 14: APPENDIX Table 5. Worldwide Altitud
Page 15: How to Reach Us: Home Page: www.fre

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