Futuristic Obsidian Group Ins V2 Save 95% Now [Z6VqDKoQ]

Learn about how M-Engineering used the INS V2 in our 992 Carrera 4S in this RennList post here.

Lead time is approximately 1 week to ship from time of order. 

GNSS + IMU with online pose estimation filter.

This device is a multi-functional sensor that merges two main components:

-An Inertial Measurement Unit (IMU) that has a 3-axis accelerometer and a 3-axis gyroscope. The accelerometer measures changes in velocity along three perpendicular axes (x, y, and z), and the gyroscope detects changes in rotational position (pitch, roll, and yaw) along the same axes.

-A Global Navigation Satellite System (GNSS) receiver, which communicates with satellites to determine the sensor's location on Earth.

• 200Hz 32-bit Position (Latitude, Longitude, Altitude)
• 400Hz 32-bit Velocity (Body X, Body Y, Body Z, and 2D Speed)
• 400Hz 32-bit Body Frame Acceleration (Gravity Removed) (X, Y, Z) with online acceleration bias compensation
• 400Hz 32-bit Angular Rate (X, Y, Z) with online gyro bias compensation
• 400Hz 16-bit Orientation (Roll, Pitch, Yaw (Degrees))
• 100Hz "MoTeC GPS" simulation option for integration with MoTeC M1 ECU applications with locked firmware (GT-R, Lamborghini, etc...)
• CNC aluminum enclosure with Deutsch ASL connection

What makes this sensor unique is its onboard sensor fusion algorithm. This sophisticated software combines the different measurements from the IMU and the GNSS to produce very accurate and fast updates on the sensor's position, orientation, and movement.

The sensor fusion algorithm also corrects for biases (systematic errors) in the accelerometer and gyroscope measurements, ensuring even more accurate data.

Moreover, the device can calculate the velocities in the sensor's (or the vehicle's) own frame of reference, which can be extremely useful for understanding and controlling its movement.

Purpose:

The main objective with this sensor is to put cutting-edge, high-performance sensor fusion algorithms into the hands of motorsport integrators and motorsport engineers without having to deal with sensor calibration, embedded systems, or understanding the sensitivity of MEMS IMU’s, specifically.

Functional Overview:

The sensor fusion algorithm that runs on this sensor is an Extended Kalman Filter (EKF). An EKF is a filter that combines data from multiple sensors and provides a best guess estimate of the position, orientation, and velocity of the vehicle.

User Manual:

INS User Manual (.pdf) update 9/3/2023

Software Integration:

MoTeC Dash Channel Configuration File (.chx) (MoTeC Dash Channel File) update 9/3/2023

MoTeC Dash CAN Configuration File Version 43 (.cc9) (MoTeC Dash Channel Config) update 9/3/2023

Universal CAN Database Configuration File Version 43 (.dbc) (Bosch Motorsport et. others) update 9/3/2023

MoTeC M1 Build Project Hardware Revision 2 (.m1prj) (MoTeC M1 Build Project for source code) update 9/3/2023 (Includes INS, and IMU)

MoTeC M1 INS/IMU Test Package (MoTeC M1 Package for INS / IMU Testing) update 6/1/2023

Hardware Integration:

INS 3D File Version 2 (.step) update 11/1/2022