Hi, Standard Range Plus Model 3 (version 19.16.2) SOC ~75%, 15 mi (24 km) warm-up 3711 (empty weight) + 250 (driver) + 15 (EVSE, patch kit) ~= 3976 lbs (8,747 kg) 77F (25C) asphalt road surface wind 0 mph, 9:09 PM (21:09) CST The acceleration data will be used to calculate the velocity. Then I'll add the EPA roll-down drag coefficients to calculate the total force on the car and eventually the vehicle HP (kW). This will be for both chill and standard modes. Bob Wilson ps. Those 'down spikes' are the end of the maximum acceleration runs. I targeted 80 mph as my ending speed because the car sounds an excessive speed alarm at 90 mph. Yes, I could have disabled the speed alarm but earlier GPS measured runs showed 80 mph was adequate to our goals. I'm using a Gulf Coast Data Concepts, Human Activity Monitor: Code: ;Title, http://www.gcdataconcepts.com, X16-MPU-ham, ADXL345, MPU-9250 ;Version, 1191, Build date, Nov 15 2016, SN:CCDC3016B4874F1 ;Start_time, 2019-06-05, 21:09:12.423 ;Temperature, -999.00, deg C, Vbat, 4174, mv ;MPU SR, 200,Hz, Accel sens, 4096,counts/g, Gyro sens, 16,counts/dps, Mag SR, 10,Hz, Mag sens, 1666,counts/mT ;Deadband, 50, counts ;DeadbandTimeout, 0,sec ;Time, Ax, Ay, Az, Gx, Gy, Gz, Mx, My, Mz 0.004486,-170,1156,-4192,5,-54,-1 0.018432,96,1210,-3916,-21,-20,-9,-311,-383,-506 0.038421,-396,1242,-4240,-20,-34,0 0.058410,-370,1302,-4166,-25,-13,-8 0.078399,680,1450,-4722,-17,-10,-7,-304,-371,-506 0.098419,-384,1138,-4572,-18,-18,0 0.118408,-584,1142,-4106,-8,1,-7 0.138397,124,978,-3978,7,15,-8 0.158386,250,1096,-4122,16,1,-5 0.178406,-640,1222,-4154,17,-12,3,-296,-387,-514 Time - seconds from start of data file. Use the header to get the 'real time' clock and date. Ax - side to side acceleration Ay - front to rear acceleration Az - top to bottom, gravity, which we use to scale 1 G Gx - rotation about the door axis Gy - rotation about the front to rear axis Gz - rotation around a vertical axis Mx - magnetic field along door axis My - magnetic field along front to rear axis Mz - magnetic field along the vertical axis MEMS accelerometer data are noisy so I used a 7 element Gaussian filter (0.063, 0.250, 0.375, 0.250, 0.063) to do a weighted average. Unlike a linear average, this preserves the local peaks while significantly reducing the noise. Each data file has 16,000 data samples covering about 5 minutes which puts a significant load on the OpenSource spreadsheet. Somewhat arbitrary, I used 500 counts, 500/4096 ~= 12.2% G, to trim the non-acceleration elements reducing the samples to 2,185 which was easily handled by the spreadsheet.
So this is what the velocity looks like: Remember, my car has a heavy driver, the EVSE, and a tire patch kit. Bob Wilson ps. The mass is 1,803 kg
Both Chill and Standard mode acceleration metrics: HP - the inertial power needed to accelerate the car and contents drag - the power needed to handle rolling, transmission, and aerodynamic drag Total HP - the total power needed at the drive wheels Bob Wilson
