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Dinesh B. Sonawane

Bio: Dinesh B. Sonawane is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Air brake & Compressed air. The author has an hindex of 1, co-authored 2 publications receiving 15 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, an approximate first order linear model including time lag is proposed to predict the pressure transients in the brake system and the transfer function of the time lag was then approximated and used to design various controllers such as proportional, proportionalintegral and proportional-integral derivative controllers.
Abstract: One of the most important systems that ensure the safe operation of vehicles traveling on roadways is the brake system. Most commercial vehicles such as buses and trucks are equipped with an air brake that uses compressed air as the energy transmitting medium. The conventional air brake has a significant time lag that affects its performance. An electro-pneumatic brake system uses an electric signal to modulate the air pressure in the brake system and it has been shown to significantly reduce the time lag associated with the conventional air brake system. This paper deals with the application of a PID controller for regulating the air pressure in an electro-pneumatic brake. An approximate first order linear model including time lag is proposed to predict the pressure transients in the brake system. The transfer function of the time lag is then approximated and used to design various controllers such as proportional, proportional-integral and proportional-integral-derivative controllers. These controllers are implemented on the experimental setup and their performances are compared.

16 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, a collision avoidance algorithm was developed using a sliding mode controller (SMC) and compared to one developed using linear full state feedback in terms of performance and controller effort.
Abstract: An important aspect from the perspective of operational safety of heavy road vehicles is the detection and avoidance of collisions, particularly at high speeds. The development of a collision avoidance system is the overall focus of the research presented in this paper. The collision avoidance algorithm was developed using a sliding mode controller (SMC) and compared to one developed using linear full state feedback in terms of performance and controller effort. Important dynamic characteristics such as load transfer during braking, tyre-road interaction, dynamic brake force distribution and pneumatic brake system response were considered. The effect of aerodynamic drag on the controller performance was also studied. The developed control algorithms have been implemented on a Hardware-in-Loop experimental set-up equipped with the vehicle dynamic simulation software, IPG/TruckMaker®. The evaluation has been performed for realistic traffic scenarios with different loading and road conditions. The Ha...

17 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigate the hysteresis characteristics of a pneumatic braking system for multi-axle heavy vehicles (MHVs) and show that the delay of each loop gets longer with the increase of pedal opening, and a quadratic relationship exists between them.
Abstract: This study aims to investigate the hysteresis characteristics of a pneumatic braking system for multi-axle heavy vehicles (MHVs). Hysteresis affects emergency braking performance severely. The fact that MHVs have a large size and complex structure leads to more nonlinear coupling property of the pneumatic braking system compared to normal two-axle vehicles. Thus, theoretical analysis and simulation are not enough when studying hysteresis. In this article, the hysteresis of a pneumatic brake system for an eight-axle vehicle in an emergency braking situation is studied based on a novel test bench. A servo drive device is applied to simulate the driver’s braking intensions normally expressed by opening or moving speed of the brake pedal. With a reasonable arrangement of sensors and the NI LabVIEW platform, both the delay time of eight loops and the response time of each subassembly in a single loop are detected in real time. The outcomes of the experiment show that the delay time of each loop gets longer with the increase of pedal opening, and a quadratic relationship exists between them. Based on this, the pressure transient in the system is fitted to a first-order plus time delay model. Besides, the response time of treadle valve and controlling pipeline accounts for more than 80% of the loop’s total delay time, indicating that these two subassemblies are the main contributors to the hysteresis effect.

16 citations

Journal ArticleDOI
01 Apr 2020-Energies
TL;DR: Simulation results show that the proposed coordination control strategy can effectively reduce torque fluctuation and vehicle jerk during mode switching.
Abstract: The electro-hydraulic composite braking system of a pure electric vehicle can select different braking modes according to braking conditions. However, the differences in dynamic response characteristics between the motor braking system (MBS) and hydraulic braking system (HBS) cause total braking torque to fluctuate significantly during mode switching, resulting in jerking of the vehicle and affecting ride comfort. In this paper, torque coordination control during mode switching is studied for a four-wheel-drive pure electric vehicle with a dual motor. After the dynamic analysis of braking, a braking force distribution control strategy is developed based on the I-curve, and the boundary conditions of mode switching are determined. A novel combined pressure control algorithm, which contains a PID (proportional-integral-derivative) and fuzzy controller, is used to control the brake pressure of each wheel cylinder, to realize precise control of the hydraulic brake torque. Then, a novel torque coordination control strategy is proposed based on brake pedal stroke and its change rate, to modify the target hydraulic braking torque and reflect the driver’s braking intention. Meanwhile, motor braking torque is used to compensate for the insufficient braking torque caused by HBS, so as to realize a smooth transition between the braking modes. Simulation results show that the proposed coordination control strategy can effectively reduce torque fluctuation and vehicle jerk during mode switching.

15 citations

Journal ArticleDOI
Xiuheng Wu1, Liang Li1, Xiangyu Wang1, Xiang Chen1, Shuo Cheng1 
TL;DR: An LMS-based adaptive feedforward amplitude-phase regulator is first employed to reduce the frequency of the high frequency pressure oscillation to low frequency’s, followed by applying an output feedback controller based on high gain observer to mitigate the low frequency oscillations to realize steady state.

13 citations

Journal ArticleDOI
TL;DR: Comparative experiments with non-transfer methods indicate that the proposed framework obtains a higher accuracy in recognizing BIL in the car following scenario, especially when sufficient data are not available.
Abstract: Accurately recognizing braking intensity levels (BIL) of drivers is important for guaranteeing the safety and avoiding traffic accidents in intelligent transportation systems. In this paper, an instance-level transfer learning (TL) framework is proposed to recognize BIL for a new driver with insufficient driving data by combining Gaussian Mixture Model (GMM) and importance weighted least squares probabilistic classifier (IWLSPC). By considering the statistic distribution, GMM is applied to cluster the data of braking behaviors into three levels with different intensities. With the density ratio calculated by unconstrained least-square importance fitting (ULSIF), LSPC is modified as IWLSPC to transfer the knowledge from one driver to another and recognize BIL for a new driver with insufficient driving data. Comparative experiments with non-transfer methods indicate that the proposed framework obtains a higher accuracy in recognizing BIL in the car following scenario, especially when sufficient data are not available.

12 citations