In this paper, the sine-cosine optimization algorithm (SCO) is used to solve the shape optimization of a vehicle clutch lever. The design problem is posed for the shape optimization of a clutch lever with a mass objective function and a stress constraint. Actual function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, grasshopper optimization algorithm, and sine-cosine algorithm are used for shape optimization. The results show the ability of the sine-cosine optimization algorithm to optimize automobile components in the industry.
This paper considers fuzzy logic and proportional integral derivative based multi-objective optimization of a non-linear active suspension system of a 4 × 4 in-wheel motor-driven electric vehicle by using the non-dominated sorting genetic algorithm II. The active suspension system of the electric vehicle and its controllers are optimized to achieve International Organization for Standardization2631-1 ride comfort and health criteria, also providing the actual working conditions such as roll angle and tire load transfers simultaneously for driving safety. In this regard, a non-linear full electrical vehicle model with quadratic tire and cubic suspension stiffnesses with 11 degrees of freedom and a seat-driver model with 5 degrees of freedom are implemented and optimized regarding seven objective functions determined from the root mean square of head and seat accelerations, crest factor , vibration dose value , the ratio of head and seat accelerations, the ratio of the upper torso and seat acceleration, root mean square upper torso acceleration, and root mean square of suspension, tire, and in-wheel motor displacements. The design variables of the optimization problem are chosen as the stiffnesses and damping coefficients of the suspension, in-wheel motors, and seat, as well as the parameters of the proportional derivative and fuzzy logic controllers. The obtained results demonstrate that significant improvements can be achieved by using a controller over the passive systems. It is also noted that the fuzzy logic controller improves ride comfort and the health criterion over proportional derivative system up to 13%, while the load transfer ratio index showed no adverse change between models concerning the rollover condition. The outcomes of this work clearly state that significant improvements, in terms of vibration exposure, can be achieved with the help of reducing the vibration amplitude of an in-wheel motor-driven electrical vehicle active suspension system by using multi-objective optimization considering a non-linear full vehicle model and realistic working conditions such as tire load transfer and vehicle body roll during cornering circumstances. Thus, obtained results are of utmost importance for manufacturers about the active suspension design process providing both a safe and comfortable driving of in-wheel driven electric vehicles.
In this paper, the sine-cosine optimization algorithm (SCO) is used to solve the shape optimization of a vehicle clutch lever. The design problem is posed for the shape optimization of a clutch lever with a mass objective function and a stress constraint. Actual function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, grasshopper optimization algorithm, and sine-cosine algorithm are used for shape optimization. The results show the ability of the sine-cosine optimization algorithm to optimize automobile components in the industry.
Today, with the increasing transition to electric vehicles (EVs), the design of highly energy-efficient vehicle architectures has taken precedence for many car manufacturers. To this end, the energy consumption and recovery rates of different powertrain vehicle architectures need to be investigated comprehensively. In this study, six different powertrain architectures—four independent in-wheel motors with regenerative electronic stability control (RESC) and without an RESC, one-stage gear (1G) transmission, two-stage gear (2G) transmission, continuously variable transmission (CVT) and downsized electric motor with CVT—were mathematically modeled and analyzed under real road conditions using nonlinear models of an autonomous hydrogen fuel-cell electric vehicle (HFCEV). The aims of this paper were twofold: first, to compare the energy consumption performance of powertrain architectures by analyzing the effects of the regenerative electronic stability control (RESC) system, and secondly, to investigate the usability of a downsized electrical motor for an HFCEV. For this purpose, all the numerical simulations were conducted for the well-known FTP75 and NEDC urban drive cycles. The obtained results demonstrate that the minimum energy consumption can be achieved by a 2G-based powertrain using the same motor; however, when an RESC system is used, the energy recovery/consumption rate can be increased. Moreover, the results of the article show that it is possible to use a downsized electric motor due to the CVT, and this powertrain significantly reduces the energy consumption of the HFCEV as compared to all the other systems. The results of this paper present highly significant implications for automotive manufacturers for designing and developing a cleaner electrical vehicle energy consumption and recovery system.
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