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Avery Blaschko
CSI SAFE 2016 v16.0.2 Build 1153 دانلود نرم افزار آنالیز و طراحی دال و پی (فونداسیون) بتنی در سایت آنی دانلود به صورت رایگان همراه با لینک مستقیم و فیلم ...
CSI SAFE دانلود نرم افزار CSI SAFE 2016 v16.0.2 Build 1153 نرم افزاری مفید و کاربردی جهت طراحی کف بتنی post-tension و سیستم های بنیادی ...
Any vehicle's driving and riding characteristics are of utmost importance during the design process. These characteristics are dependent on parameters related to modelling the vehicle as a body and suspension that include spring, absorber, sprung and un-sprung mass of the vehicle mass, all with stiffness and shock absorption features taken into account for both the vehicle body with suspension and for the tires [1-5]. The primary goals of a vehicle's suspension system are to provide good handling, as well as comfort, safety, decreased fatigue, and a reduction in health issues caused by road profiles. However, adopting a passive-type suspension system makes it relatively difficult to achieve a high level of comfort and optimal handling at the same time [6-9].
Shock absorption and suspension stiffness needs for handling and ride comfort have opposite requirements as vehicular motion bears opposition forces generated by the road profile affecting the overall body-related aerodynamics. The vehicle's suspension system acts to stabilize the vehicle motion under torque and inertial forces variation as a function of road profile with trajectory and speed as important parameters. Thus, vehicle design and development now include simulation of vehicle models on a regular basis, which not only shortens the time it takes to go from concept to production but also saves money and time over prototyping. Additionally, it enables performance optimization to create safer vehicles with the best handling and ride comfort features that can be automatically managed as a function of the road profile by autonomous and intelligent vehicles [10, 11].
There is considerable work on autonomous vehicles covering their suspension control in relation to cruise control at adaptive speeds and the selection of automation level-related dynamics of driving (comfort, handling) in conjunction with collision avoidance and safety strategy. Cruise control used by autonomous vehicles, particularly adaptive cruise control, is related to the longitudinal motion of the vehicle and affects suspension dynamics and gets affected by road profile and trajectories for a particular speed, which affects the comfort and handling of the vehicle [12]. Much work needs to be done relating driving comfort, vehicle handling and suspension control under an integrated strategy, which enables an autonomous vehicle to select the best mode of driving as a function of road profile, taking vehicle speed into account, to ensure stability and safety [13, 14].
Mobility benefits greatly from autonomous driving since highly automated vehicles will help drivers relieve some of the difficult responsibilities while providing safer and more dependable driving away from distraction and poor reaction times that some drivers experience under specific circumstances. The Advanced Driving Assistance System (ADAS) is advantageous for automated driving [15].
Most drivers are not trained professional vehicle pilots, making it very difficult to accomplish comfort and handling goals and safe driving. Even the most talented drivers struggle to do some tasks without the aid of sophisticated mechatronic systems. The mechatronic systems provide comprehensive information (fused) from the installed advanced sensors regarding the vehicle's status, road, and environment. This information is gathered and processed at very high speed, enabling very quick reaction times with the ability to be applied to specific vehicle components. Safety can be increased significantly with intra- and inter-vehicle networking, which, when paired with sensors and intelligent systems, will prevent many issues and accidents brought on by people. Thus, intelligently correlating road profiles with speed and the vehicle suspension system in autonomous vehicles can contribute effectively to safety enhancement and reduction of accidents [16, 17].
The instruction layer provides necessary commands to the application layer regarding actions required to achieve optimal stability and comfort. The application layer actively and dynamically exchanges data and affects the powertrain operations related to vehicle movements and trajectories. This can all be carried out automatically and intelligently in the autonomous vehicle environment, ensuring the safety and reliability of the travelled journey and balancing between handling, stability and comfort [20].
Due to the recent development in the automotive industry and vehicular control and computing power, using optimization, simulation, and intelligent algorithms, focus on the vehicle suspension design for both comfort and handling become possible using techniques ranging from numerical analysis to simulation of vehicular operations [21-23]. Active and semi-active suspension systems for automotive applications are designed and tested using mechatronics systems. Sensors and actuators are used within the vehicle control environment to enable higher safety and optimum comfort levels [24-27].
For the suspension system of the vehicles, especially autonomous ones, to perform optimally over different road profiles with different roughness and elevations and to enable road better road handling to ensure safety, variable stiffness to damping ratios need to be considered in selecting driving mode automatically by the self-driving vehicle. This reliable approach provides a mechanism to optimize vehicle movement based on road profile and speed [28-32].
From Equations (1) and (2), SLVR can be calculated as in equation (3), which correlates the important variables affecting vehicle driving in terms of comfort, handling, and safety.
To further examine the effect of road profile and suspension stiffness on the damping ratio regarding the performance, reliability, handling, and safety of autonomous vehicles, the second derivative in equation (4) is used to evaluate the acceleration of sprung mass as the vehicle travels along a profiled road.
This research aims to employ equations (3) and (4) along with the results of the simulations as input to an automatic optimization and selection system that will enable active suspension and tire control, giving autonomous vehicles comfort, safety, and handling. Such a methodology could also be improved, refined, and applied to the design of autonomous cars.
At a smooth road profile with normal elevation (E=1), tire spring and suspension spring vary in parallel but opposite manner (closer to each other than the case where k:c=20), as shown in Fig. (14). The k:c=0.27 ratio indicates an optimized vehicle condition, where suspension stiffness is lower than damping, which reflects a setting for reliable and safe road handling.
These findings for k:c=0.27 is further supported by the sprung mass acceleration responses for the three considered road profiles, as shown in Figs. (17-19). The plots show the massive difference in acceleration to overcome road profile values and enable safer and more reliable driving through a significant increase in acceleration from E=1 through to E=5.
This work uses MATLAB simulation to establish criteria for optimization of vehicle-road interaction through varying road profiles and suspension stiffness to damping ratios. The work presented a new technique to optimize comfort and handling, using the intersection between tire spring and suspension spring length variation and analysing the subsequent sprung mass acceleration. The work considered a vehicle speed of 60km.h needs to further consider other velocities and different sprung and un-sprung mass parameters, various tire stiffness and a wider range of road profiles to enable a reliable automatic control system to select driving mode as per road profile and function of vehicle parameters. Vehicle design and development now include simulation of vehicle models on a regular basis, which not only shortens the time it takes to go from concept to production but also saves money and time over prototyping. Additionally, it enables performance optimization to create safer cars with the best handling and ride comfort features that can be automatically modified depending on the road profile by autonomous and intelligent cars. Using an integrated strategy, driving comfort, vehicle handling, and suspension control enable an autonomous vehicle to select the ideal mode of driving as a function of road profile.
Intelligently matching road profiles with speed and the vehicle suspension system in autonomous vehicles can effectively contribute to safety enhancement and accident reduction. Thus, a switching mechanism per road profile can be implemented based on the simulated characteristics at the three levels of road profile and different suspension stiffness to damping coefficients.
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