EFFECT OF EMULSION SBR PREPARED BY ASYMMETRIC REVERSIBLE ADDITION-FRAGMENTATION TRANSFER AGENT ON PROPERTIES OF SILICA-FILLED COMPOUNDS

ABSTRACT The development of ultra-high-performance tires that satisfy fuel efficiency, traction, handling performance, and abrasion resistance has gained significant importance in the tire industry. Solution SBR has been used as a raw material, owing to its useful characteristics (e.g., narrow dispersity controllable microstructure and chain-end functionalization). In a recent improvement, emulsion SBR (ESBR), a high-molecular-weight compound with narrow dispersity, has been reported for application in the tire tread compounds. In particular, S,S-dibenzyl trithiocarbonate (DBTC) reversible addition-fragmentation transfer (RAFT) ESBR has exhibited excellent abrasion resistance and fuel efficiency in unfilled and carbon black–filled vulcanizates. However, owing to the symmetrical structure of DBTC RAFT ESBR, the polymer chain was shortened by the reaction of a silane coupling agent with trithiocarbonate, leading to poor abrasion resistance and fuel efficiency in the case of silica-filled vulcanizates. In this study, benzyl (4-methoxyphenyl) trithiocarbonate (BMPTC), an asymmetric RAFT agent that promotes unilateral polymer growth, was synthesized and used in the polymerization of BMPTC RAFT ESBR. Chain cleavage was not observed. Upon application to silica-filled vulcanizates, BMPTC RAFT ESBR exhibited improved abrasion resistance (by 9%), improved fuel efficiency (by 20%), and improved wet traction performance (by 10%) compared with the DBTC RAFT ESBR.

Coordinated control of distributed drive electric vehicle by TVC and ESC based on function allocation

Safe and comfortable driving experience includes the improvement of handling performance and stability control. This paper proposed a coordinated controller based on the function allocation for the handling performance and stability of distributed drive electric vehicles. The proposed controller has three layers. The upper control layer designs a dynamic stability envelope boundary suitable for various driving conditions through the phase plane method, and on this basis, the function allocation rules of torque vector control (TVC) strategy and electronic stability control (ESC) strategy were formulated. The medium control layer used the robust [Formula: see text] dynamic output feedback control method and the improved particle swarm optimization (PSO) parameter self-adjusting method to calculate the additional yaw moment required by the TVC strategy and the ESC strategy, respectively. The two types of additional yaw moment are implemented by the in-wheel motor and the hydraulic brake mechanism respectively. The lower control layer optimized the four-wheel torque and braking force based on the optimal tire load rate using the quadratic programming method. The proposed coordinated controller was performed in the CarSim/Simulink co-simulation platform and tested in a real vehicle platform. The results show that the proposed controller can improve the vehicle dynamic response according to the driver’s intention, thus bringing the better handling performance and stability.

A New Torque Distribution Control for Four-Wheel Independent-Drive Electric Vehicles

Torque distribution control is a key technique for four-wheel independent-drive electric vehicles because it significantly affects vehicle stability and handling performance, especially under extreme driving conditions. This paper, which focuses on the global yaw moment generated by both the longitudinal and the lateral tire forces, proposes a new distribution control to allocate driving torques to four-wheel motors. The proposed objective function not only minimizes the longitudinal tire usage, but also make increased use of each tire to generate yaw moment and achieve a quicker yaw response. By analysis and a comparison with prior torque distribution control, the proposed control approach is shown to have better control performance in hardware-in-the-loop simulations.

Configuration development and optimization of hydraulically interconnected suspension for handling and ride enhancement

In this study, among 180 possible hydraulically interconnected suspension configurations, non-symmetric cases were eliminated and 24 potential configurations were selected for further investigation. A 14-DOF vehicle model capable of generating handling and ride motions is developed. At different manoeuvres and road inputs, the handling and ride performances are investigated for 24 configurations. Six hydraulic parameters are then optimized by the application of genetic algorithm in order to improve the ride. The handling performance is also investigated and results have shown that only four configurations provide better ride and handling performances simultaneously. The bounce acceleration response is shown to be reduced up to 47% for the four selected configurations. The roll and pitch angle responses were also reduced around 3% and 18% respectively. Four optimized configurations were also investigated under two sever ride and handling manoeuvres. It is shown that, for the vehicle with the optimized interconnected hydraulic suspension, the bounce acceleration response for a random road test is reduced up to 27% and the roll angle is reduced up to 18% for a side wind test.

Pengategorian Provinsi Berdasarkan Kelompok Sukses dan Gagal dalam Penanganan Pandemik Covid-19 di Indonesia Menurut Analisis Diskriminan

An assessment of categorizing the handling of Covid-19 by the Regional Government is needed, this categorization includes the handling performance (KP) and the death rate (TK) of Covid-19. This was done to see how serious the local government is in handling Covid-19. The approach in this study uses a descriptive approach, this approach aims to describe or describe the categorization of provinces based on groups that have succeeded and failed in handling the Covid-19 pandemic in Indonesia. In this research, the method used is quantitative method. The quantitative approach used is discriminant analysis. The conclusion of this study is that the discriminant function formed in this study is Z = 0.893 KP + 0.451 TK. The results of eigenvalues in this study indicate that the magnitude of Canonical Correlation is 0.797 or the amount of Square Canonical Correlation (CR2) = (0.797) 2 or equal to 0.635. So it can be concluded that 63.5% of the variation between groups of successful and failed provinces can be explained by the discriminant variables of the KP and TK ratios. The view of the matrix structure in this study shows that the amount of loading for KP is 0.842 and the amount of loading for TK is 0.332. The two variables of the Covid 19 handling ratio are high enough so that the discriminant score can be interpreted as a measure of the success of the handling of Covid 19 at the Provincial Government. Meanwhile, the results of the classification matrix show that 32 observations have been classified correctly and only two observations are classified incorrectly, namely the observations number 18 and 19, so the classification accuracy is (32/34) or 94.1%.