Abstract

Reduction in vertical acceleration is crucial for car manufacturers. This parameter evaluates the comfort index. Moreover, the handling index is another feature that must be under investigation. The suspension system has an essential impact on these two indices. A hybrid intelligent switching hydraulically interconnected suspension (HISHIS) is proposed. The parallel configuration is combined with the diagonal configuration in the suspension system. A mode selection strategy is discussed to select the layout between diagonal and parallel configurations. The only mode of parallel configuration is called Anti-pitch configuration. The diagonal configuration has three modes, including Anti-roll, Anti-oversteering, and Anti-vibration configuration. According to the mode selection strategy, one of these three diagonal configuration modes might be selected. The origin of roll and pitch generation is inertia force and road inputs. Hopfield neural network can recognize the origin of roll and pitch generation. Therefore, the performance of valves will change according to Hopfield neural network recognition. The results of different maneuvers show the improvement at each targeted parameter in various tasks independently. The data logger gathered the acceleration of the vehicle in real-world conditions. However, the margins of the selection strategy block are multi-objective optimized with a genetic algorithm to reach better responses in real-world conditions. The roll angle, yaw rate, allowable exposure time, and pitch angle are improved by 63%, 5%, 40%, and 99% on average. Also, optimizing the selection strategy improves the allowable exposure time by 9%. Obviously, by combining two layouts, it is possible to have a flexible situation to improve ride comfort and handling situations. In addition, there is a conditional strategy to select different layouts and modes to reach a better response.

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