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The wheel slip control systems are able to control the braking force more accurately and can be adapted to different vehicles more easily than conventional braking control systems. In order to achieve the superior braking performance through the wheel slip control, real-time information such as tire braking force at each wheel is required. In addition, the optimal target slip values need to be determined depending on the braking objectives such as minimum braking distance, stability enhancement, etc. In this paper, a vehicle stability control system is developed based on the braking monitor, wheel slip controller, and optimal target slip assignment algorithm. The braking monitor estimates the tire braking force, lateral tire force, and brake disk-pad friction coefficient utilizing the extended Kalman filter. The wheel slip controller is designed based on the sliding mode control method. The target slip assignment algorithm is proposed to maintain the vehicle stability based on the direct yaw-moment controller and fuzzy logic. A hardware-in-the-loop simulator (HILS) is built including electrohydraulic brake hardware and vehicle dynamics software. The effectiveness of the proposed stability control system is demonstrated through the HILS experiment.

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In this paper, track tension monitoring methodology is developed so that the track tension can be estimated under various maneuvering tasks such as longitudinal driving on sloping and/or rough roads, turning on flat or sloping roads, etc. The real-time information of the track tension is very important for tracked vehicles because the track tension is closely related to the maneuverability and the durability of tracked vehicles. In the case of longitudinal driving, a modified 3 DOF dynamics model is derived for tracked vehicles and is utilized for estimating the tractive force and track tension. In the case of turning, kinetic models for six road-wheels are obtained and used for calculating the track tension around the sprocket. This method does not require tuning of the turning resistance, which makes it difficult to estimate the track tension in turning. The estimation performance of the proposed methods is verified through simulations of the Multi-Body Dynamics tool. The simulation results demonstrate the effectiveness of the proposed method under various maneuvering tasks of tracked vehicles.

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