Target State Optimization: Drivability Improvement for Vehicles with Dual Clutch Transmissions

Vehicles with dual clutch transmissions (DCT) are well known for their comfortable drivability since gear shifts can be performed jerklessly. The ability of blending the torque during gear shifts from one clutch to the other, making the type of automated transmission a perfect alternative to torque converters, which also comes with a higher efficiency. Nevertheless, DCT also have some drawbacks. The actuation of two clutches requires an immense control effort, which is handled in the implementation of a wide range of software functions on the transmission control unit (TCU). These usually contain control parameters, which makes the behavior adaptable to different vehicle and engine platforms. The adaption of these parameters is called calibration, which is usually an iterative time-consuming process. The calibration of the embedded software solutions in control units is a widely known problem in the automotive industry. The calibration of any vehicle subsystem (e.g., engine, transmission, suspension, driver assistance systems for autonomous driving, etc.) requires costly test trips in different ambient conditions. To reduce the calibration effort and the accompanying use of professionals, several approaches to automize the calibration process are proposed. Due to the fact that a solution is desired which can optimize different calibration problems, a generic metaheuristic approach is aimed. Regardless, the scope of the current research is the optimization of the launch behavior for vehicles equipped with DCT since, particularly at low speeds, the transmission behavior must meet the intention of the driver (drivers tend to be more perceptive at low speeds). To clarify the characteristics of the launch, several test subject studies are performed. The influence factors, such as engine sound, maximal acceleration, acceleration build-up (mean jerk), and the reaction time, are taken into account. Their influence on the evaluation of launch with relation to the criteria of sportiness, comfort, and jerkiness, are examined based on the evaluation of the test subject studies. According to the results of the study, reference values for the optimization of the launch behavior are derived. The research contains a study of existing approaches for optimizing driving behavior with metaheuristics (e.g., genetic algorithms, reinforcement learning, etc.). Since the existing approaches have different drawbacks (in scope of the optimization problem) a new approach is proposed, which outperforms existing ones. The approach itself is a hybrid solution of reinforcement learning (RL) and supervised learning (SL) and is applied in a software in the loop environment, and in a test vehicle

Loss of auditory sensitivity from inner hair cell synaptopathy can be centrally compensated in the young but not old brain

AbstractA dramatic shift in societal demographics will lead to rapid growth in the number of older people with hearing deficits. Poorer performance in suprathreshold speech understanding and temporal processing with age has been previously linked with progressing inner hair cell (IHC) synaptopathy that precedes age-dependent elevation of auditory thresholds. We compared central sound responsiveness after acoustic trauma in young, middle-aged, and older rats. We demonstrate that IHC synaptopathy progresses from middle age onward and hearing threshold becomes elevated from old age onward. Interestingly, middle-aged animals could centrally compensate for the loss of auditory fiber activity through an increase in late auditory brainstem responses (late auditory brainstem response wave) linked to shortening of central response latencies. In contrast, old animals failed to restore central responsiveness, which correlated with reduced temporal resolution in responding to amplitude changes. These findings may suggest that cochlear IHC synaptopathy with age does not necessarily induce temporal auditory coding deficits, as long as the capacity to generate neuronal gain maintains normal sound-induced central amplitudes

Target State Optimization: Drivability improvement for vehicles with dual clutch transmissions

Vehicles with dual clutch transmissions (DCT) are well known for their comfortable drivability since gear shifts can be performed jerklessly. The ability of blending the torque during gear shifts from one clutch to the other, making the type of automated transmission a perfect alternative to torque converters, which also comes with a higher efficiency. Nevertheless, DCT also have some drawbacks. The actuation of two clutches requires an immense control effort, which is handled in the implementation of a wide range of software functions on the transmission control unit (TCU). These usually contain control parameters, which makes the behavior adaptable to different vehicle and engine platforms. The adaption of these parameters is called calibration, which is usually an iterative time‐consuming process. The calibration of the embedded software solutions in control units is a widely known problem in the automotive industry. The calibration of any vehicle subsystem (e.g., engine, transmission, suspension, driver assistance systems for autonomous driving, etc.) requires costly test trips in different ambient conditions. To reduce the calibration effort and the accompanying use of professionals, several approaches to automize the calibration process are proposed. Due to the fact that a solution is desired which can optimize different calibration problems, a generic metaheuristic approach is aimed. Regardless, the scope of the current research is the optimization of the launch behavior for vehicles equipped with DCT since, particularly at low speeds, the transmission behavior must meet the intention of the driver (drivers tend to be more perceptive at low speeds). To clarify the characteristics of the launch, several test subject studies are performed. The influence factors, such as engine sound, maximal acceleration, acceleration build‐up (mean jerk), and the reaction time, are taken into account. Their influence on the evaluation of launch with relation to the criteria of sportiness, comfort, and jerkiness, are examined based on the evaluation of the test subject studies. According to the results of the study, reference values for the optimization of the launch behavior are derived. The research contains a study of existing approaches for opti‐ mizing driving behavior with metaheuristics (e.g., genetic algorithms, reinforcement learning, etc.). Since the existing approaches have different drawbacks (in scope of the optimization problem) a new approach is proposed, which outperforms existing ones. The approach itself is a hybrid solu‐ tion of reinforcement learning (RL) and supervised learning (SL) and is applied in a software in the loop environment, and in a test vehicle

Subcortical neural synchrony and absolute thresholds predict frequency discrimination independently

The neural mechanisms of pitch coding have been debated for more than a century. The two main mechanisms are coding based on the profiles of neural firing rates across auditory nerve fibers with different characteristic frequencies (place-rate coding), and coding based on the phase-locked temporal pattern of neural firing (temporal coding). Phase locking precision can be partly assessed by recording the frequency-following response (FFR), a scalp-recorded electrophysiological response that reflects synchronous activity in subcortical neurons. Although features of the FFR have been widely used as indices of pitch coding acuity, only a handful of studies have directly investigated the relation between the FFR and behavioral pitch judgments. Furthermore, the contribution of degraded neural synchrony (as indexed by the FFR) to the pitch perception impairments of older listeners and those with hearing loss is not well known. Here, the relation between the FFR and pure-tone frequency discrimination was investigated in listeners with a wide range of ages and absolute thresholds, to assess the respective contributions of subcortical neural synchrony and other age-related and hearing loss-related mechanisms to frequency discrimination performance. FFR measures of neural synchrony and absolute thresholds independently contributed to frequency discrimination performance. Age alone, i.e., once the effect of subcortical neural synchrony measures or absolute thresholds had been partialed out, did not contribute to frequency discrimination. Overall, the results suggest that frequency discrimination of pure tones may depend both on phase locking precision and on separate mechanisms affected in hearing loss