Interior Noise Prediction and Analysis of Heavy Commercial Vehicle Cab

Author(s):  
Shuming Chen ◽  
Dengfeng Wang ◽  
Jiqiang Song ◽  
Gangping Tan ◽  
Bingwu Lu
Author(s):  
Xiaohua Zeng ◽  
Zhenwei Wang ◽  
Dafeng Song ◽  
Dongpo Yang

The coordination control of a transmission system has gradually attracted more attention with the development of hybrid electric vehicles. However, nonlinear coupling of multiple power sources, superposition of different dynamic characteristics in multiple components, and withdrawal and intervention for a power-split powertrain with a two-speed automated manual transmission (AMT) gearbox can cause jerk and vibration of the transmission system during the shift, which has higher requirements and challenges for the overall performance improvement of the system. This paper designs a novel, robust, augmented H∞ shift control strategy for a power-split system with a two-speed AMT gearbox of a heavy commercial vehicle and verifies the strategy’s effectiveness with simulations and experiments. First, the dynamic plant model and kinetic equations are established, and the shift is divided into five stages to clearly reveal the jerk and vibration problem. Based on augmented theory, a robust H∞ shift control strategy is proposed. Shift coordination is transformed into a speed tracking problem, and state variable and disturbance are reconstructed to obtain a new augmented system. Simulation and hardware-in-the-loop test are carried out to verify the effectiveness of the strategy, which mainly includes simulation of pneumatic actuator and H∞ control strategy. Results show that the proposed H∞ control strategy can greatly reduce the jerk of the transmission system. The jerk produced by the proposed strategy is decreased from 20.4 to 4.07 m/s3, leading to a substantial improvement of 80%. Therefore, the proposed strategy may offer a theoretical reference for the actual vehicle controller during the shift.


Author(s):  
E Latorre Iglesias ◽  
J Xia ◽  
ME Farooq ◽  
A Bistagnino ◽  
J Sapena

Noise emissions play a key role in the development of environment-friendly rolling stock. Noise limits given by EU directives for interoperability purposes but also by internal directives of the different countries where any kind of rolling stock operates have to be respected for train approval. Exterior noise predictions are used nowadays to validate the design of new rolling stock. These predictions are used within the companies to evaluate the different design options, to optimize costs, to assess the risks and for virtual certification in cases where existing products are modified. Potentially predictions could be used in the future for a complete virtual certification of the train allowing to decrease or even to completely avoid the noise tests that are currently carried out by the train manufacturers. As a consequence, the cost of the certification process will be reduced. One of the challenges for a complete virtual certification is the assessment of uncertainties in the predictions as probably this will not be accepted by the stakeholders without a defined and validated uncertainty assessment. This work presents a methodology to estimate the uncertainty of the predictions of train noise emissions. An example of the application of the proposed framework for uncertainty evaluation is provided for a typical suburban rolling stock showing the feasibility of its use for railway exterior noise predictions but potentially also for interior noise calculations and for different applications other than railway.


2014 ◽  
Vol 7 (1) ◽  
pp. 150-156 ◽  
Author(s):  
Hengjia Zhu ◽  
Yuliang Yang ◽  
Yu Yang ◽  
Jian Zeng ◽  
Yunqing Zhang

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