Publications

Coordination between friction brake system, individual-wheel drive electric motors and tire inflation pressure system is considered. To coordinate vehicle subsystems, optimization-based control allocation is used. The influence of subsystem coordination on criteria of vehicle dynamics (braking distance, RMSE of longitudinal acceleration, RMSE of yaw rate, sideslip angle) and energy consumption and losses (recuperated energy during maneuver and tire energy dissipation) were analyzed for straight-line braking and brake-in-turn maneuvers by simulation investigation. The proposed control system was investigated using HIL test rig with hardware components of friction brake system and tire inflation pressure system.

The paper addresses methodology of the assessment of vehicle dynamics on the basis of a set of cost functions. The proposed concept covers different domains like longitudinal, lateral and vertical dynamics with a possibility to deduce a complex cost function having three main attributes: (i) dimensionless form, (ii) range from 0 to 1, and (iii) weighting factors for each individual domain. The attributes (i) and (ii) are subjected to the comparison of baseline, reference, and actual values of corresponding parameters of vehicle dynamics like acceleration, yaw rate, slip and others. The attribute (iii) links to the choice of weighting factors from the analysis of vehicle maneuvers. Application fields of the developed individual and complex cost functions are assessment of vehicle performance and stability, optimization of relevant control systems, and choice of proper control strategies / tuning of control gains by autonomous or cooperative operation of several systems of vehicle dynamics control. The paper introduces the implementation of the proposed methodology by the example of Electronic Stability Program (ESP) system. Case studies illustrate results of the calculation of the cost functions for the avoidance and slalom maneuvers. The corresponding computational procedures are based on full vehicle software simulator, validated with experiments on the real vehicle.

Coordination between friction brake system, individual-wheel drive electric motors and tire inflation pressure system is considered. To coordinate vehicle subsystems, optimization-based control allocation is used. The influence of subsystem coordination on criteria of vehicle dynamics (braking distance, RMSE of longitudinal acceleration, RMSE of yaw rate, sideslip angle) and energy consumption and losses (recuperated energy during maneuver and tire energy dissipation) were analyzed for straight-line braking and brake-in-turn maneuvers by simulation investigation. The proposed control system was investigated using HIL test rig with hardware components of friction brake system and tire inflation pressure system.

The paper addresses methodology of the assessment of vehicle dynamics on the basis of a set of cost functions. The proposed concept covers different domains like longitudinal, lateral and vertical dynamics with a possibility to deduce a complex cost function having three main attributes: (i) dimensionless form, (ii) range from 0 to 1, and (iii) weighting factors for each individual domain. The attributes (i) and (ii) are subjected to the comparison of baseline, reference, and actual values of corresponding parameters of vehicle dynamics like acceleration, yaw rate, slip and others. The attribute (iii) links to the choice of weighting factors from the analysis of vehicle maneuvers. Application fields of the developed individual and complex cost functions are assessment of vehicle performance and stability, optimization of relevant control systems, and choice of proper control strategies / tuning of control gains by autonomous or cooperative operation of several systems of vehicle dynamics control. The paper introduces the implementation of the proposed methodology by the example of Electronic Stability Program (ESP) system. Case studies illustrate results of the calculation of the cost functions for the avoidance and slalom maneuvers. The corresponding computational procedures are based on full vehicle software simulator, validated with experiments on the real vehicle.