Adaptive and reconfigurable slip vectoring control in electric vehicles with four in-wheel motors

Controllability, maneuverability, fault-tolerance/isolation and safety are significantly enhanced in electric vehicles (EV) with distributed actuator sets. A new non-model based adaptive and reconfigurable control architecture, called Slip Vectoring, is presented to regulate speed and yawrate in a fully EV equipped with four in-wheel induction motors (IWMs). Distributed Electric Powertrain (EP) configurations with distributed IWMs offer redundancy and enhance the vehicle maneuverability, since the propulsion can be integrated with a continuous yaw-motion control by bidirectional differential torques. Nested proportional and integral controls are designed for the motor current control inputs on the basis of speed and yaw-rate regulation errors and acceleration measurements. Given the allocation matrix and a suitable constraint accounting for the longitudinal force and yaw-moment requests, the actuators redundancy is dealt with by minimizing the overall slip vector norm, so that each IWM is given a suitable slip reference according to the slip vectoring allocation, corresponding to four angular speed references when the vehicle speed is constant. In order to drive independently each in-wheel motor speed to its reference, four decentralized current-pair inputs are provided to each motor. The motor speed feedback control loops lead to exponentially convergent wheel load torque estimates, which are compensated by the delivered motor torques. In this way, the torque-slip operating conditions is online monitored at each wheel, to determine in which region (linear/nonsaturated or nonlinear/saturated) of the torque/slip characteristics each tire is operating. This allows for the allocation of four different torques at steady-state according to the individual uncertain tire-road friction and vertical load conditions, so that the load torque requirements are matched for each wheel. Consequently, the slip vectoring allocation can be reconfigured in order to force the 4IWMs to operate within the linear tire region: the allocation can be equalized on the basis of the actual wheel load conditions or the 4IWMs set can be reconfigured by an electronic online powertrain switching among several possible layouts. The control reconfigurability includes Fault-Detection and -Isolation (FDI) as a special case: the FDI is allowed by the monitoring capabilities of the algorithm, while the possibility to de-select a faulted motor provides Fault-Tolerance (FT). Consequently, the initial driving-mode selection can be automatically adjusted and restored among eighteen configurations (2WD/4WD, front/rear differentials) to meet the safety requirements of linear torque/slip behavior. A global asymptotic and local exponential slip regulation is obtained when open-loop slip references are given. Sufficient conditions for local exponential convergence of the speed and yaw-rate regulation errors are obtained in the case of constant vehicle longitudinal speed and zero yaw-rate references. The convergence proof leads to the definition of a new overall stability index which is monitored online. Then, an automatic longitudinal speed reduction can be performed with the goal of keeping the stability index within a predetermined range. Realistic CarSim co-simulations with Matlab-Simulink are presented to validate the proposed strategy: (i) a preliminary open-loop slip ramp is performed for wheel limits characterization; (ii) the standard moose-test maneuver illustrates yaw-rate tracking performance on dry and wet asphalt, assisted by the continuous differential actions from the four in-wheel torques; the adaptivity features of the controller with respect to the torque loads are shown; the same maneuver is performed in six driving mode configurations to evaluate the path tracking performances; a comparison with a vehicle with an internal combustion engine (ICE) and with a conventional (ESC) Electronic Stability Control is also provided; (iii) two fault-detection and -isolation algorithms with induction motors smooth switching are illustrated; one in-wheel motor or two coxial in-wheel motors at a time can be online de-selected from the actuator set; (iv) a snowy uphill path illustrates the non model-based speed reduction driven by the stability index monitoring; (v) the slip vectoring equalization algorithm is examined in the case of longitudinal and lateral nominal wheel load imbalances. An experimental setup is designed to validate the proposed Slip Vectoring strategy and to show the possibility to monitor the tire-operating conditions, with the proposed methodology, from wheel angular speed real measurements.