Gm Global Technolgoy Operations, Inc.

The University of Waterloo

Seyedeh Asal Nahidi

SeyedAlireza Kasaiezadeh Mahabadi

Bakhtiar Brian Litkouhi

Hualin Tan

James Heath Holbrook

Ehsan Asadi

Naser Mehrabi

Reza Hajiloo

Saurabh Kapoor

Yubiao Zhang

Shamim Mashrouteh

Seyedalireza Kasaiezadeh Mahabadi

John Randall Yost

Hassan Askari

Michael W Neal

Ruixing Long

Reza Zarringhalam

Amir Khajepour

Kausalya Singuru

Jin-Jae Chen

Ibrahim A Badiru

Bharath Pattipati

Douglas J Spry

Arash Hashemi

Gianmarc Coppola

Xueying Kang

Isaac Tabatschnic

Lapo Frascati

Ramakrishna Kamath Vijayakumar

Ehsan Mohammadbagher

Cody Dunham

A vehicle steering control system including a road wheel angle sensor for detecting a road wheel angle, a steering feedback motor for rotating a steering wheel in response to the road wheel angle and for generating a steering torque value in response to a physical rotation of the steering wheel by a vehicle driver, a processor for receiving the road wheel angle and the steering torque value, for estimating a steering wheel angle in response to the steering torque value and for generating a validated steering angle in response to a difference between the road wheel angle and the steering wheel angle being less than a threshold value, and a steering controller for controlling the steering of a vehicle in response to the validated steering angle.

Steering wheel angle sensor estimation and validation system

A method for controlling a steer-by-wire system, comprising receiving vehicle data and a steering request from a vehicle, determining whether a steering road wheel actuator of the vehicle has failed using the vehicle data, in response to determining that the steering road wheel actuator of the vehicle has failed, determining a target wheel slip of the vehicle based on the steering request, maintaining the target wheel slip of the vehicle while the vehicle is in motion; and adjusting a wheel speed of at least one wheel of the vehicle based on a feedback signal, wherein the feedback signal is indicative of a road wheel angle while the vehicle is in motion.

Architecture and method for steer-by-wire failure backup using direct yaw control actuators

A system for managing chassis and driveline actuators of a motor vehicle includes a control module executing program code portions that: cause sensors to obtain vehicle state information, receive a driver input and generate a desired dynamic output based on the driver input and the vehicle state information, and then estimate actuator actions based on the vehicle state information, generate one or more control action constraints based on the vehicle state information and estimated actuator actions, generate a reference control action based on the vehicle state information, the estimated actions of the one or more actuators and the control action constraints, and integrate the vehicle state information, the estimated actuator actions, desired dynamic output, reference control action and the control action constraints to generate an optimal control action that falls within a range of predefined actuator capacities and ensures driver control of the vehicle.

Architecture and model predictive control-based methodology to manage chassis and driveline actuators

A method for vehicle motion control includes receiving sensor data from a plurality of sensors of a vehicle and monitoring a vehicle response of the vehicle using the sensor data. The vehicle response is represented by a plurality of vehicle-response signals. The method further includes fusing the plurality of vehicle-response signals to obtain at least one fused signal. The method further includes determining whether to activate a vehicle stability control of the vehicle based on the at least one fused signal and commanding the vehicle to activate the vehicle stability control in response to determining to activate the vehicle stability control of the vehicle based on the at least one fused signal.

Data fusion-centric method and system for vehicle motion control

A system for adaptive tire force prediction in a motor vehicle includes a control module that executes program code portions that receive real-time static and dynamic data from motor vehicle sensors, that model forces at each tire of the motor vehicle at one or more incremental time steps, that estimate actual forces at each tire of the motor vehicle at each of the one or more incremental time steps, that adaptively predict tire forces at each tire of the motor vehicle at each of the one or more incremental time steps, that generate one or more control commands for actuators of the motor vehicle, that capture discrepancies between real-time force estimations and nominal force calculations at each tire of the motor vehicle, and that apply compensation parameters to reduce tracking errors in the one or more control commands to the one or more actuators of the motor vehicle.

Architecture and methodology of adaptive tire force prediction for integrated vehicle motion control

Systems and methods for determining whether a vehicle is in an understeer or oversteer situation. The system includes a controller circuit coupled to an IMU and an EPS, and programmed to: calculate, for a steered first axle, an axle-based pneumatic trail for using IMU measurements and EPS signals and estimate a saturation level as a function of a distance between the axle-based pneumatic trail and zero. The system estimates, for an unsteered second axle, an axle lateral force curve with respect to a slip angle of the second axle, and a saturation level as a function of when the axle lateral force curve with respect to the slip angle transitions from positive values to negative values. The saturation level of the first axle and the second axle are integrated. The system determines that the vehicle is in an understeer or oversteer situation as a function of the integrated saturation levels.

Systems and methods for determining whether a vehicle is in an understeer or oversteer situation

A system for managing vehicle body and wheel motion control with a dual clutch differential includes sensors and actuators disposed on the vehicle, the sensors measuring real-time static and dynamic data and the actuators altering static and dynamic behavior of the motor vehicle. A control module executes program code portions stored in memory. The program code portions receive the real-time static and dynamic data; selectively prioritize torque output from a prime mover of the vehicle through the differential to driven wheels of the vehicle to control a body and the driven wheels; model and estimate clutch torque for each clutch of the dual clutch differential; model and estimate a joint clutch torque, a tire force, and corner torque; and generate a torque output for each clutch of the dual clutch differential that is selected to maintain one or more of body control, wheel control, and stability of the motor vehicle.

Management of body and wheel motion controls with dual clutch differential

A driver command predictor includes a controller, multiple sensors, and a command prediction unit. The controller is configured to command an adjustment of multiple motion vectors of a vehicle relative to a roadway in response to multiple actual driver commands and multiple future driver commands. The actual driver commands are received at a current time. The future driver commands are received at multiple update times. The update times range from the current time to a future time. The sensors are configured to generate sensor data that determines multiple actual states of the vehicle in response to the motion vectors as commanded. The command prediction unit is configured to generate the future driver commands at the update times in response to a driver model. The driver model operates on the actual driver commands and the actual states to predict the future driver commands at the update times.

Driver command prediction

A system includes a primary control module, a stability status module, and a supervisory control module. The primary control module is configured to determine at least one control action for at least one of an electronic limited slip differential and an aerodynamic actuator of a vehicle based on a driver command. The stability status module is configured to determine whether at least one component of the vehicle is stable or unstable based on an input from a sensor on the vehicle. The at least one component includes at least one of a vehicle body, a front axle, a rear axle, front wheels, and rear wheels. The supervisory control module is configured to adjust the at least one control action when the at least one component is unstable.

System and method for controlling electronic limited slip differential and active aerodynamic actuator on vehicle

A vehicle motion control system includes one or more input devices for generating one or more input signals associated with data indicative of a motion of the vehicle. The system further includes a computer, which has one or more processors. The computer further includes a non-transitory computer readable storage medium for storing instructions, such that the processor is programmed to compare a current tire state and a current tire prediction model to the data indicative of the motion of the vehicle. The processor is further programmed to calculate in real-time an adjusted tire state and an adjusted tire prediction model. The processor is further programmed to generate in real-time one or more actuation signals based on the adjusted tire state and the adjusted tire prediction model. The actuators in real-time adjust the motion of the vehicle in response to the actuator receiving the actuation signal from the processor.

Vehicle motion control system using real-time tire state correction

An aerodynamic deflector on the vehicle is repositionable. An actuator is coupled with the aerodynamic deflector. A controller configured to: detect a performance mode of operation of the vehicle; determine a requested lateral acceleration; calculate a control adjustment of the aerodynamic deflector to generate a downforce to achieve the requested lateral acceleration and maximize lateral grip of the vehicle; and operate the actuator to effect the control adjustment of the aerodynamic deflector to generate the downforce on the vehicle.

System and method for optimal vehicle downforce allocation

A system for supervisory control for eAWD and eLSD in a motor vehicle includes a control module, and sensors and actuators disposed on the motor vehicle. The sensors measure real-time motor vehicle data, and the actuators alter behavior of the motor vehicle. The control module receives the real-time data; receives one or more driver inputs to the motor vehicle; determines a status of a body of the motor vehicle; determines a status of axles of the motor vehicle; determines a status of each wheel of the motor vehicle; and generates a control signal to the actuators from the driver inputs and the body, axle, and wheel statuses. The control module also exercises supervisory control by actively adjusting constraints on the control signal to each of the actuators where actively adjusting constraints on the control signal alters boundaries of control actions in response to the one or more driver inputs.

Supervisory control for e-AWD and e-LSD

Systems and methods for vehicle motion control are provided. The method includes: calculating a correction factor using one of three different sets of operations when the vehicle is performing a limit handling maneuver, wherein the correction factor is calculated using a first set of operations when the vehicle is operating in an understeer state, calculated using a second set of operations when the vehicle is operating in an oversteer state, and calculated using a third set of operations when the vehicle is operating in a neutral steer state; adjusting a desired lateral acceleration and a desired yaw rate by applying the correction factor to account for a reduced level of friction experienced by the vehicle when traveling on a non-ideal friction surface; calculating optimal control actions based on the adjusted desired lateral acceleration and adjusted desired yaw rate; and applying the optimal control actions with vehicle actuators during vehicle operations.

System and method to estimate maximum lateral acceleration and yaw rate in limit handling maneuvers in low-friction surfaces

Systems and methods for controlling a vehicle are provided. The systems and methods include a sensor system and a processor configured to execute program instructions, to cause the at least one processor to: receive yaw rate values, lateral acceleration values and longitudinal velocity values for the vehicle from the sensor system, determine side slip angle parameter values based on the yaw rate values, lateral acceleration values and longitudinal velocity values, determine phase portrait angles based on the side slip angle parameter values and the yaw rate values, wherein the phase portrait angles each represent an angle between yaw rate and side slip angle for the vehicle in a phase portrait of yaw rate and side slip angle, detect or predict vehicle instability based at least on the phase portrait angles, and when vehicle instability is detected or predicted, control motion of the vehicle to at least partly correct the vehicle instability.

Systems and methods for predicting and detecting vehicle instability

A system includes a clutch state module and a clutch torque module. The clutch state module is configured to determine whether a clutch of an electronic limited slip differential is locked or unlocked. The electronic limited slip differential couples an engine of a vehicle to left and right wheels of the vehicle. The clutch torque module is configured to estimate an actual torque transferred by the clutch using a first clutch torque model when the electronic limited slip differential is unlocked, and estimate the actual clutch torque using a second clutch torque model when the electronic limited slip differential is locked. The second clutch torque model is different than the first clutch torque model.

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North York, Canada

Seyedeh Asal Nahidi