Spring-damper assembly
    11.
    发明授权

    公开(公告)号:US10131196B2

    公开(公告)日:2018-11-20

    申请号:US15404886

    申请日:2017-01-12

    Abstract: A spring-damper assembly for a suspension corner employed in a vehicle having a vehicle body and a road wheel includes a fluid spring configured to suspend the vehicle body relative to the road wheel. The spring-damper assembly also includes a damper configured to attenuate compression and rebound oscillations of the fluid spring. The spring-damper assembly additionally includes a spring-seat housing configured to retain the fluid spring and establish a position of the fluid spring relative to the damper. The spring-seat housing includes an inner surface defining a contour configured to guide the fluid spring upon compression thereof around the damper and define a non-linear stiffness of the fluid spring. A vehicle having such a spring-damper assembly is also provided.

    Adaptive in-drive updating of vehicle energy consumption prediction

    公开(公告)号:US11867521B2

    公开(公告)日:2024-01-09

    申请号:US17672806

    申请日:2022-02-16

    Abstract: A system for adaptive in-drive updating, for a vehicle travelling on a route, includes a controller adapted to obtain a pre-drive energy consumption prediction for the route, via an energy consumption predictor. An in-drive updating module is selectively executable by the controller at a timepoint during the route at which a completed portion of the route has been traversed and a remaining portion remains untraversed. The controller is adapted to obtain an actual energy consumption for segments in the completed portion of the route. The controller is adapted to obtain at least one modification factor based on a comparison of the actual energy consumption and the pre-drive energy consumption prediction for the segments in the completed portion of the route. The pre-drive energy consumption prediction for the remaining portion of the route is adjusted based on the modification factor.

    VEHICLE CONTROL USING NEURAL NETWORK CONTROLLER IN COMBINATION WITH MODEL-BASED CONTROLLER

    公开(公告)号:US20220204018A1

    公开(公告)日:2022-06-30

    申请号:US17136411

    申请日:2020-12-29

    Abstract: A vehicle control system for automated driver-assistance includes a model-based controller that generates a first control signal to alter an operation of a plurality of actuators of a vehicle based on a reference trajectory for the vehicle, and a present state of the vehicle and actuators. The vehicle control system further includes a neural network controller that generates a second control signal to alter the operation of the actuators of the vehicle based on a reference trajectory for the vehicle, and the present state of the vehicle and actuators. The vehicle control system further includes a combination module that combines the first control signal and the second control signal to operate the actuators based on a combined signal.

    Spring module with negative and positive stiffness springs

    公开(公告)号:US10189327B2

    公开(公告)日:2019-01-29

    申请号:US15433277

    申请日:2017-02-15

    Abstract: A strut assembly for a suspension corner employed in a vehicle having a vehicle body and a road wheel includes a damper. The strut assembly also includes an elastic unit having at least one spring module acting in concert with the damper to suspend the vehicle body relative to the road wheel. Each spring module has a positive stiffness spring arranged in parallel with a negative stiffness spring. A vehicle that has a suspension corner employing the elastic unit and is configured to maintain contact between the road wheel and the road surface and provide isolation of vibration between the road wheel and the vehicle body is also contemplated.

    SYSTEM FOR TUNING A TRAJECTORY TRACKING CONTROLLER FOR AN AUTOMOTIVE VEHICLE

    公开(公告)号:US20240034349A1

    公开(公告)日:2024-02-01

    申请号:US17874451

    申请日:2022-07-27

    Abstract: A system for tuning a trajectory tracking controller for a vehicle includes a trajectory planner configured to generate the planned trajectory and to output one or more planned trajectory components representative of the planned trajectory, a model predictive controller including an internal model and an optimizer, and a tuning neural network configured to receive the one or more planned trajectory components and one or more measured trajectory components and to produce weights for a cost function. The internal model is configured to receive a predicted control input from the optimizer and the one or more measured trajectory components and to produce a predicted output. The optimizer utilizes a cost function and is configured to receive the weights for the cost function and a predicted error and to produce the predicted control input, wherein the predicted error is a selected one of the planned trajectory components minus the predicted output.

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