Mechanics Based Design of Structures and Machines ( IF 3.9 ) Pub Date : 2021-05-03 , DOI: 10.1080/15397734.2021.1911664 Jony Javorski Eckert 1 , Elvis Bertoti 1 , Ludmila Corrêa de Alkmin e Silva 1 , Franco Giuseppe Dedini 1
Abstract
In the present work, a computational routine was developed in order to optimize the shifting strategies implemented in a Gear Shift Indicator to assist the driver of manual transmission vehicles according to a desired driving style. In order to achieve this goal, a simulation algorithm was developed to estimate the fuel consumption and acceleration performance of a vehicle equipped with a 5-speed manual gearbox propelled by a 1.4 L engine when submitted to the FTP-72 driving cycle. A multi-objective Genetic Algorithm was then employed to solve the optimization problem for both fuel consumption and performance. Among the set of optimized solutions, 3 shifting strategies were selected for experimental evaluation on a chassis dynamometer. The experiments showed that the strategy with focus on fuel economy was able to save 10.7% of fuel, being the best performance strategy responsible for enhancing the vehicle acceleration in 8.33%, when compared to the standard strategy provided by the vehicle manufacturer. Finally, the best-compromised solution presented 6.4% fuel-savings with an acceleration performance similar to the best performance strategy.
中文翻译:
在手动变速器车辆的换档指示系统中使用通过 i-AWGA 优化的换档策略的实验验证
摘要
在目前的工作中,开发了一个计算程序,以优化换档指示器中实施的换档策略,以根据所需的驾驶风格协助手动变速器车辆的驾驶员。为实现这一目标,开发了一种模拟算法来估算配备 5 速手动变速箱的车辆在提交 FTP-72 驾驶循环时的油耗和加速性能,该变速箱由 1.4 L 发动机驱动。然后采用多目标遗传算法来解决油耗和性能的优化问题。在一组优化的解决方案中,选择了 3 种换档策略在底盘测功机上进行实验评估。实验表明,以燃油经济性为重点的策略能够节省 10.7% 的燃油,与车辆制造商提供的标准策略相比,这是负责将车辆加速度提高 8.33% 的最佳性能策略。最后,最佳折衷方案节省了 6.4% 的燃料,加速性能与最佳性能策略相似。