On the Vehicle Sideslip Angle Estimation: A Literature Review of Methods, Models, and Innovations
AbstractTypical active safety systems that control the dynamics of passenger cars rely on the real-time monitoring of the vehicle sideslip angle (VSA), together with other signals such as the wheel angular velocities, steering angle, lateral acceleration, and the rate of rotation about the vertical axis, which is known as the yaw rate. The VSA (also known as the attitude or “drifting” angle) is defined as the angle between the vehicle’s longitudinal axis and the direction of travel, taking the centre of gravity as a reference. It is basically a measure of the misalignment between vehicle orientation and trajectory; therefore, it is a vital piece of information enabling directional stability assessment, such as in transience following emergency manoeuvres, for instance. As explained in the introduction, the VSA is not measured directly for impracticality, and it is estimated on the basis of available measurements such as wheel velocities, linear and angular accelerations, etc. This work is intended to provide a comprehensive literature review on the VSA estimation problem. Two main estimation methods have been categorised, i.e., observer-based and neural network-based, focussing on the most effective and innovative approaches. As the first method normally relies on a vehicle model, a review of the vehicle models has been included. The advantages and limitations of each technique have been highlighted and discussed. View Full-Text
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Chindamo, D.; Lenzo, B.; Gadola, M. On the Vehicle Sideslip Angle Estimation: A Literature Review of Methods, Models, and Innovations. Appl. Sci. 2018, 8, 355.
Chindamo D, Lenzo B, Gadola M. On the Vehicle Sideslip Angle Estimation: A Literature Review of Methods, Models, and Innovations. Applied Sciences. 2018; 8(3):355.Chicago/Turabian Style
Chindamo, Daniel; Lenzo, Basilio; Gadola, Marco. 2018. "On the Vehicle Sideslip Angle Estimation: A Literature Review of Methods, Models, and Innovations." Appl. Sci. 8, no. 3: 355.
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