In this paper, a nonlinear control approach of an innovative engine cooling system for vehicles is presented. The electrically driven coolant pump and a servo-controlled bypass valve as control inputs, however, are su...
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ISBN:
(纸本)9781479932740
In this paper, a nonlinear control approach of an innovative engine cooling system for vehicles is presented. The electrically driven coolant pump and a servo-controlled bypass valve as control inputs, however, are subject to saturation due to physical limitations of the maximum pump volume flow and the limited opening section of the bypass valve. Based on a control-oriented system representation, a robust decentralized control employing sliding-mode techniques is proposed: an input-output linearizing control is designed for the engine outlet temperature, whereas an exact linearization is performed for the engine inlet temperature. At this control design, the given actuator limitations are explicitly taken into account. The controllers are implemented with small sampling time and combined with a discrete-time Extended Kalman Filter that estimates unknown heat flows within the system. In an experimental investigation, the performance of two alternative stabilizing control laws is compared: a linear stabilizing control law as reference and the robust sliding-mode approach leading to a nonlinear error dynamics. The obtained results highlight the effectiveness and the control performance of the proposed robust control strategy.
This paper discusses an integral slidingmode algorithm for yaw rate control of a torque-vectoring fully electric vehicle with individually controlled motor drives. The overall controlstructure is presented and the i...
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ISBN:
(纸本)9781479932740
This paper discusses an integral slidingmode algorithm for yaw rate control of a torque-vectoring fully electric vehicle with individually controlled motor drives. The overall controlstructure is presented and the integral slidingmode formulation is derived starting from the yaw moment balance equation of the vehicle. The performance of the controller, continuously active in order to track a set of reference understeer characteristics, is evaluated against that of the baseline vehicle (i.e. the vehicle without yaw rate control) in ramp steer and step steer maneuvers. Simulation results show a good tracking of the reference yaw rate deriving from the adoption of the integral slidingmodecontroller. Moreover, ease of implementation and robustness against model uncertainties make this controller particularly suitable for this type of application.
There are two theoretical methods by which a two wheeled vehicle oriented in tandem can be stabilized: dynamic stabilization and control moment gyroscope (CMG) stabilization. Dynamic stabilization utilizes tactical st...
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ISBN:
(纸本)9781479932740
There are two theoretical methods by which a two wheeled vehicle oriented in tandem can be stabilized: dynamic stabilization and control moment gyroscope (CMG) stabilization. Dynamic stabilization utilizes tactical steering techniques to trigger a lean in the vehicle in the intended direction for balancing, while CMG stabilization employs the reactive precession torque of a high speed flywheel about an axis that will act to balance the vehicle. Of these two, CMG stabilization offers greater advantages for static vehicles. This paper proposes a first order slidingmodecontroller (SMC) design to control the CMG and stabilize a bicycle at zero-forward velocity. This study also compares the SMC method to a PID controller to validate the advantages of the SMC controller for the highly non-linear system dynamics of static stabilization. The result of two experimental setups are presented and discussed. The first experimental platform is a single degree of freedom (DOF) inverted pendulum and the second is a three DOF bicycle.
Automotive powertrain control strategies are a key component of the software design process for vehicle systems. During implementation of control algorithms on real systems, errors often arise that prove costly if the...
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ISBN:
(纸本)9781479932740
Automotive powertrain control strategies are a key component of the software design process for vehicle systems. During implementation of control algorithms on real systems, errors often arise that prove costly if they are not detected until the Verification & Validation process. Thus, it is advantageous to mitigate potential uncertainties early on in the design. Specifically, in this paper, we present the control algorithm derivation with the direct incorporation of uncertainty from the system model. We incorporate an unknown parameter representing significant model uncertainty and design to that scenario using a nonlinear, discrete-time slidingcontrol strategy. Additionally, we incorporate an adaptation law to estimate and update the unknown parameter online in order to decrease the control actuation effort. A Simulink representation of the cold start engine emissions process is used as a case study on which the control and adaptation strategy is demonstrated. Simulation results demonstrate that this adaptive formulation yields superior performance over its non-adaptive counterpart by successfully estimating the unknown model parameters and driving tracking error to zero in steady-state.
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