Abstract: Systems, methods, and computer-readable storage media for a dynamic Ackermann geometry control system. The system receives, at a processor aboard a tractor of an articulated vehicle, vehicle information associated with ongoing movement of the articulated vehicle as well as a driver optimization preference. The system then executes an Ackerman control algorithm, with inputs such as the vehicle information and/or at least one feedback item. The outputs of the Ackerman control algorithm can include estimations of tire forces for each tire of the articulated vehicle and estimations of cornering characteristics of the articulated vehicle. The system then calculates, based on the estimations of tire forces and based on the estimations of cornering characteristics, a desired Ackerman geometry for the articulated vehicle. The system then transmits a command to modify a turning angle associated with at least one wheel of the articulated vehicle.

Abstract: A braking arrangement for a vehicle includes a source of compressed air, a drive axle for the vehicle, a brake associated with the drive axle and connected to the source of compressed air by an air line, an operator controlled valve in the air line between the source of compressed air and the brake, a proportioning valve in the air line between the operator controlled valve and the brake. A compressor is driven by the drive axle or a drive shaft of the vehicle and has an outlet connected to a control port of the proportioning valve.

Abstract: The invention relates to a method for controlling a flow from a source of pressurized air to an air bag of a pneumatic suspension arrangement in a vehicle. The method comprises obtaining a set of vehicle condition signals comprising at least two vehicle condition signals, each vehicle condition signal being indicative of an individual current condition associated with said vehicle. The method further comprises, on the basis of said set of vehicle condition signals, determining whether or not there is a need to supply the air bag with air from the source of pressurized air. The method further comprises, in response to determining that there is not a need to supply the air bag with air from the source of pressurized air, preventing pressurized air to be fed from said source of pressurized air to said air bag.

Abstract: Method for updating at least one vehicle model parameter and at least one tire parameter in at least one chassis control unit of a vehicle, based on tire sensor information collected by a tire sensor placed on a tire. The method includes the steps of: collecting tire sensor information; updating the at least one vehicle model parameter based on updating at least one tire parameter, updating one tire parameter being based on the tire sensor information.

Abstract: A method for updating a configuration of a braking arrangement in a vehicle is provided. The method comprises obtaining sensor data indicative of a status of the vehicle and/or of the braking arrangement during at least a part of a braking operation performed by the braking arrangement. The method further comprises predicting, based on the obtained sensor data, at least one component that are part of the braking arrangement. The method further comprises in response to detecting that the configuration of the braking arrangement does not comply with the at least one component, updating the configuration to be based on the at least one component.

Abstract: A method for detecting a flat spot of a tire of a first wheel of a vehicle. The method comprises obtaining a plurality of measurements indicative of an actuation and/or a motion of at least part of a suspension arrangement. The suspension arrangement is arranged to provide suspension for the first wheel. The method further comprises detecting that the tire has a flat spot by determining that the plurality of measurements fulfills one or more predetermined conditions.

Abstract: A method for braking one or more trailers in a tractor-trailer combination. The method comprises establishing a maximum continuous brake pressure for trailer brakes of wheels of the one or more trailers of the tractor-trailer combination. The method further comprises establishing an on-off cycling frequency for pulsing of the brakes of the one or more trailers of the tractor-trailer combination at brake pressures above the maximum continuous brake pressure. The method further comprises establishing applying the brakes of the one or more trailers continuously at brake pressures up to the established maximum continuous brake pressure and by pulsing according to the established on-off cycling frequency at brake pressures above the established maximum continuous brake pressure.

Abstract: Systems, methods, and computer-readable storage media for using neural networks to ensure the braking capabilities of articulated vehicles are adapted to prevent jackknifing. A system can receive operational parameters associated with both a vehicle and a trailer being towed by the vehicle. The system can also identify a current surface condition and predict, using a neural network, road conditions for a portion of the road which the vehicle is approaching. When distinctions between current and predicted, future conditions are defined, and the system can cause modification of the operational parameters of the vehicle and/or the trailer.

Abstract: Systems, methods, and computer-readable storage media for adjusting the steering geometry of a vehicle by using reinforcement learning in series with a neural network to determine when and how to adjust the steering geometry of the vehicle. A system can do this by receiving vehicle information associated with ongoing movement of the vehicle, and executing a reinforcement learning model using that vehicle information. The outputs of the reinforcement learning model can include a current driving cycle of the vehicle and a current application of the vehicle. The system then executes a machine learning model, where inputs to the machine learning model can include the outputs of the reinforcement learning model and the vehicle information. The outputs of the machine learning model can then include a wheel alignment signal.

Abstract: A levelling valve assembly for an air suspension system of a heavy vehicle is provided, including an air valve configured to allow air to either enter or escape from an air spring based on a position of a control arm of the air valve, and including a linkage rod assembly configured to translate movement between a sprung and unsprung mass of the vehicle into a rotation of the control arm to regulate a ride height of the vehicle. The linkage rod assembly further includes a spring and damper arrangement configured to dampen or block movement of the control arm not caused by a change in a mass loading of the vehicle.

Abstract: Systems, methods, and computer-readable storage media for using multi-stage machine learning algorithms to optimize tire contact patches on a vehicle. Vehicle sensors first collect vehicle information for the vehicle, and input that data into a first machine learning algorithm. The first machine learning algorithm then outputs a lateral dimension, a longitudinal dimension, and a diagonal dimension, which together identify a tire contact patch of at least one tire on the vehicle. The operator of the vehicle provides a human preference for how the vehicle operates, and a second machine learning algorithm is executed. The second machine learning algorithm inputs can include the plurality of vehicle information, the first machine learning algorithm outputs, and the human preference, and the second machine learning algorithm outputs can include a desired tire pressure of the at least one tire and an air suspension adjustment for the normal load of the vehicle.

Abstract: A method of brake management in a heavy vehicle is provided, and includes, in response to determining that a request for emergency braking is imminent, increasing an air pressure of e.g., a service brake system of the vehicle and decreasing an air pressure of e.g., a parking brake system of the vehicle. The method further includes, in response to actually receiving the request for emergency braking of the vehicle, performing an emergency braking of the vehicle by compounding both the service and parking brake systems, including further increasing the air pressure of the service brake system and further decreasing the air pressure of the parking brake system. A corresponding brake system controller, brake system, heavy vehicle, computer program and computer program product are also provided.

Abstract: Systems, methods, and computer-readable storage media for training a Recurrent Neural Network to evaluate sensor data related to a brake rotor, then diagnosing brake rotors using sensor data and the trained Recurrent Neural Network. Sensor data can include audio data, temperature data, caliper pressure data, and/or any other data related to operation of the brake rotor being evaluated. When a processor is configured to execute the trained Recurrent Neural Network, sensor inputs can be provided to the processor, with the output being a diagnosis of the brake rotor state.

Abstract: A braking arrangement for a vehicle includes a source of pressurized air, a first wheel with a first pneumatic brake arrangement including a first brake, the first brake being arranged to be engaged when connected to the source of pressurized air and disengaged when disconnected from the source of pressurized air, a second wheel with a second pneumatic brake arrangement including a second brake, the second brake being arranged to be engaged when connected to the source of pressurized air and disengaged when disconnected from the source of pressurized air, and a proportional valve between the source of pressurized air and the first brake, opening of the proportional valve being proportional to pressure in a line between the source of pressurized air and the proportional valve. The first pneumatic brake arrangement and the second pneumatic brake arrangement function differently.

Abstract: A method includes collecting wheel loads applied to wheels tires of the vehicle, from wheel sensor sets installed in the wheels, when the vehicle is in a steady state and when it is subjected to a movement computing, by a vehicle control unit, longitudinal and lateral positions of a center of gravity of the vehicle, based on vehicle parameters and the wheel loads when the vehicle in the steady state; measuring the movement; and computing, by the vehicle control unit, a height of the center of gravity, based on the movement, the vehicle parameters, the longitudinal or lateral position of the center of gravity and the wheel loads when the vehicle is subjected to the movement.

Abstract: The present disclosure relates to a method for controlling performance of a vehicle by estimating a center of gravity of the vehicle, the method comprising: receiving by a vehicle control unit, load parameters describing features of a load in the vehicle, collecting, by the vehicle control unit, a load weight measure of a load in the vehicle, from a load sensor, when the vehicle is in a steady state; and computing, by the vehicle control unit, using a neural network, longitudinal and lateral positions and height of a center of gravity of the vehicle, based on the load parameters and the load weight measure.

Abstract: An electronic control unit is configured to collect and process sensor data comprising environment data, driver signals and vehicle state signals by a physics-based processing module the sensor data to produce a physics-based route classification and a physics-based driver's driving style classification, and by a neural network module trained for predicting a machine learning route classification and a machine learning driver's driving style classification; provide the physics-based route classification and the physics-based driver's driving style classification, and the machine learning route classification and the machine learning driver's driving style classification, to a feedback module configured to estimate a driving recommendation for the driver; provide emulated driver signals, based on the driving recommendation, and the environment data, to a vehicle simulation module to provide simulated vehicle state signals; process by the physics-based processing module the emulated driver signals and the simul

Abstract: A motion control system for controlling one or more torque generating devices on a heavy-duty vehicle, the system comprising a primary sensor system with a primary sensor control unit configured to interpret an output signal of the primary sensor system, one or more tire sensor devices mounted on, in, or in connection to, one or more tires of the heavy-duty vehicle, and a tire sensor control unit configured to interpret an output signal of the one or more tire sensor devices, wherein the motion control system is arranged to base motion control of the heavy-duty vehicle on output data of the tire sensor control unit in case of malfunction in the primary sensor system and/or in the primary sensor control unit, and on output data of the primary sensor control unit otherwise.

Abstract: A control system for controlling one or more torque generating devices on a heavy-duty vehicle comprising a primary sensor system with a primary sensor control unit configured to interpret an output signal of the primary sensor system, wherein the primary sensor control unit is configured to determine a first load value associated with the heavy-duty vehicle, and one or more tire sensor devices mounted on one or more tires of the heavy-duty vehicle, and a tire sensor control unit configured to interpret an output signal of the one or more tire sensor devices, wherein the tire sensor control unit is configured to determine a second load value associated with the heavy-duty vehicle, wherein the control system is arranged to base control of the heavy-duty vehicle on the second load value in case of malfunction in the primary sensor system and/or in the primary sensor control unit.

Abstract: Method for monitoring health status of a chassis system of a vehicle comprising a new electronic control unit, a set of sensors, and a communication bus configured to convey signal data, the new electronic control unit being configured to run a vehicle chassis system simulation module based on a vehicle main physics-based model of each subsystem of the chassis system of the vehicle, a first neural network module, a second neural network module, and a signal processing module, comprising the following steps implemented by the new electronic control unit to predict a first set of data-driven subsystem health statuses, provide a second set of physics-based subsystem health statuses, provide a set of consolidated subsystem health statuses, and depending on the set of consolidated subsystem health statuses, produce a support recommendation to correct failures indicated by the set of consolidated subsystem health statuses.