Real Time Vehicle Dynamics for Smart Driving

In last few years there has been great research to increase safety of on-road vehicles by providing information of various vehicle parameters to the user/driver while driving on road. Many algorithms have been developed to assess the vehicle run time situations and enable vehicle ECU to take decisions for autonomous driving. These algorithms are derived using data captured from sensors predominantly make use of vehicle dynamic information. The design proposed in this paper discusses capturing of two important and critical vehicle run time parameters i.) Vehicle tire pressure and the ii.) Road gradient. These parameters then help us in determining the effective fuel efficiency of the vehicle and approximate distance that user can drive with the amount of fuel remaining in the tank.

In real time situations, the road gradient is dynamically calculated by the pitch angle using the gyro sensor and calculating the vehicle gradient with the height sensors installed, while tire pressure is continuously monitored by the vehicle ECU through the pressure sensors available at the wheel end. Vehicle models are also inherited in the ECU for the calculation of parameters. These parameters are further used to compile data of the running vehicle, which accessible by the vehicle as well as the driver to comprehend the vehicle safety under the run time situations, and preventive actions can be taken well in advance.