http://www.seipub.org/VE/RSS.aspxen-US2015-0<p class="abstract">Development of Test Set for Tire Failure Emergency Braking System</p><ul><li>Pages 1-5</li><li>Author QingZhang ChenJonathan M. WeaverWei Wan</li><li>Abstract To develop tire blowout emergency braking system, one of the key problems is the test method for system calibration. By simulating the process of tire blowout, and transmitting the tire failure signal to the system, the test set carries out every performance experiments, so that the control strategy and the control value can be adjusted according to test results. After developing the tire blowout emergency braking system, we designed the tire blowout simulating device, which can release tire pressure with big flow by controlling a small flow, so that the problem of simulating big flow of tire blowout repeatedly was solved. With this device, we also can simulate the different intensity of tire blowout. The whole test system was built, and the road test was carried out. The results show that the test system can be used to develop the relative emergency braking system, and achieve the experiment of system calibration and performance evaluation.</li></ul>http://www.seipub.org/ve/PaperInfo.aspx?ID=16318Vehicle Engineeringhttp://www.seipub.org/ve/PaperInfo.aspx?ID=163182015-0<p class="abstract">Vehicle Suspension Control Using Recurrent Neurofuzzy Wavelet Network</p><ul><li>Pages 6-15</li><li>Author Shahid QamarUsman KhalidM. Bilal Quresh</li><li>Abstract The main aim of this paper is to design the controller for a vehicle suspension system to reduce the uneasiness felt by passengers which arises from road disturbances and to increase the road holding related with the movements of pitch and roll of the vehicle. This demands an accurate and quick adaptive controller to obtain such control objectives, because, the passive suspension system and semi-active suspension cannot perform better. Therefore, an adaptive Recurrent Fuzzy Wavelet Neural Network (RFWNN) based active suspension systems are designed to give better ride comfort and vehicle stability. The proposed adaptive RFWNN model combines the traditional TSK fuzzy model and the wavelet neural networks. The RFWNN controller is highly nonlinear and robust to meet the control objectives and can handle the nonlinearities faster than other conventional controllers. An online learning algorithm, which consists of parameter learning, is also presented. The learning parameters are based on the steepest-descent method, to train the proposed RFWNN. The proposed approach is used to minimize the vibrations of seat, heave pitch and roll of the vehicle when traveling on rough road. The performance of the proposed RFWNN control strategy is being assessed by comparing with passive and semi-active suspension systems.</li></ul>http://www.seipub.org/ve/PaperInfo.aspx?ID=23214Vehicle Engineeringhttp://www.seipub.org/ve/PaperInfo.aspx?ID=232142015-0<p class="abstract">Virtual Testing and Experimental Verification of Medium-Duty Truck Driveability and Rideability</p><ul><li>Pages 16-25</li><li>Author Y. Gene LiaoBrandon CardMolly O’Malle</li><li>Abstract This paper presents on- and off-road virtual testing of driveability and rideability on the Family of Medium Tactical Vehicle (FMTV) cargo trucks. Proving ground tests are also conducted to provide some experimental correlation and validation of the simulation results. The front suspension of the current baseline FMTV is a solid axle with leaf springs and shock absorbers. Two other types of suspension systems including passive and semi-active suspensions are evaluated in solid axle and fully independent configurations. The objective of this study is to evaluate the capability of virtual tests in vehicle performance. The comprehensive experiments also investigate the capabilities of various suspensions which have been considered in future FMTV design for mobility performance improvement.</li></ul>http://www.seipub.org/ve/PaperInfo.aspx?ID=24137Vehicle Engineeringhttp://www.seipub.org/ve/PaperInfo.aspx?ID=241372015-0<p class="abstract">Multimodal Braking System Based on Deceleration Control</p><ul><li>Pages 26-30</li><li>Author Mengling WuLu ZhuXiaodong Wan</li><li>Abstract This paper proposes a “Multimodal Braking System based on Deceleration Control” with deceleration as braking control objective, including dynamic brake, permanent magnetic track brake and electro-pneumatic brake. Respectively, the validity of permanent magnetic track brake and deceleration control is analyzed in detail. The result shows permanent magnet track brake can achieve multilevel control by changing the angle of magnetic axis so that service braking can be realized, which can provide the deceleration of 0.56m/s2; compared with the traditional braking system, the steady-state error of braking system based on deceleration control is less than 0.062m/s2.</li></ul>http://www.seipub.org/ve/PaperInfo.aspx?ID=26168Vehicle Engineeringhttp://www.seipub.org/ve/PaperInfo.aspx?ID=261682015-0<p class="abstract">Research on the Charging Regime of Intelligent Charger of Automotive Valve-regulated Lead-acid Battery</p><ul><li>Pages 31-37</li><li>Author Suyun LuoPeng JiaYangchun WuLei Tan</li><li>Abstract Charger has a great impact on the performance and service life of battery and charging regime is significant for intelligent charger. Researchers usually combine two or three charging methods to get a good performance charging regime, but the effect is still less than satisfactory and cannot charge and renovate the battery at the same time. This article studies on charging regime of intelligent charger based on normal charging methods character analysis of VRLA battery and references to some charger products regimes, and gives a seven phases regime including Resonant composite pulse charging, soft start, bulk charge, absorption, battery test, recondition and float. From the result shown in experiments, this charging regime resolves the problem of failing to charge and renovate batteries simultaneously, implementing a high performance charging.</li></ul>http://www.seipub.org/ve/PaperInfo.aspx?ID=30341Vehicle Engineeringhttp://www.seipub.org/ve/PaperInfo.aspx?ID=30341