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Home»Research»AFM experiments on vertical dynamics test rigs of AI-based control algorithms
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AFM experiments on vertical dynamics test rigs of AI-based control algorithms

versatileaiBy versatileaiMarch 25, 2025No Comments2 Mins Read
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AFM experiments on vertical dynamics test rigs of AI-based control algorithms

AI semi-activity suspensions for mobility (AFM) testing platforms allow real-time control of vehicle vertical dynamics. This allows for adaptation to a variety of road excitations and critical driving situations, optimizing both driving safety and ride comfort. Designing an AI-based damper controller requires a true model of vertical dynamics. Can be used for both model-based controller design and learning (AI) control methods.

Extensive experiments were conducted to characterize the vertical dynamics of AFM. In collaboration with partner KW Automotive GmbH, funded as part of the Kifahr project, the vehicle was equipped with a variety of sensors before being exposed to vertical excitation defined by a four-post test rig. This setup allows you to measure and analyze vehicle dynamics with predefined height profiles. The tests performed included harmonics and road-like excitation. The transfer function of characteristic vehicle states was estimated using sine wave excitation with increasing frequency. Chassis acceleration and wheel loads are very interesting as they can be used to quantify ride comfort and safety. Many different variables were recorded on the testbench to further support the modeling process. Not only is the acceleration of the wheels, chassis and engines interesting, but the deflection of the components also measured with a potentiometer. If the semi-active damper actuator current, four post position, velocity, acceleration, dynamic wheel load and additional auxiliary variables were added, then more than 50 signals had to be processed. Many measurement channels required recording on two different devices. For subsequent recording synchronization, specific signals were recorded on both devices, and then used to calculate delays to correct for different time bases of measurements.

The suspension limits were systematically tested in almost 100 separate experiments with different amplitudes, roll and pitch excitations, and sine wave oscillations with realistic road profiles. Two applications have been developed for ad hoc analysis, allowing time domain measurement data to be visualized and transfer functions for input and output combinations can be estimated.

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