Improved Design of Generalized Dynamic Rollover Threshold of Multi-Axial Vehicle
Heng Wei, Wei Liu, Yusen Wang, Yao Danya
Abstract
Heng Wei, Wei Liu, Yusen Wang, Yao Danya
Abstract
This paper aims at proposing an improved generalized dynamic rollover threshold of multi-axial vehicles based on lateral load transfer ratio (LTR) and providing the foundation for rollover prediction. The study is carried out by utilizing vehicle handling dynamics to build a vehicle rollover model, which takes into account the characteristics of suspension and limit equilibrium of tires' lifting-off. We developed a real-time rollover warning platform to dynamically indicate the vehicle rollover trend and compare our generalized threshold with two other common used thresholds, not only on TruckSim platform with simulation vehicle, but also on the rollover warning platform with test vehicle. Results show that on TruckSim platform, the proposed LTR is much closer to the defined LTR, especially when facing rollover, it's much more sensitive and accurate in indicating impending danger of rollover, on the rollover warning platform, three LTRs have similar trends, while the proposed LTR performs better in predicting rollover.
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This paper aims at proposing an improved generalized dynamic rollover threshold of multi-axial vehicles based on lateral load transfer ratio (LTR) and providing the foundation for rollover prediction. The study is carried out by utilizing vehicle handling dynamics to build a vehicle rollover model, which takes into account the characteristics of suspension and limit equilibrium of tires' lifting-off. We developed a real-time rollover warning platform to dynamically indicate the vehicle rollover trend and compare our generalized threshold with two other common used thresholds, not only on TruckSim platform with simulation vehicle, but also on the rollover warning platform with test vehicle. Results show that on TruckSim platform, the proposed LTR is much closer to the defined LTR, especially when facing rollover, it's much more sensitive and accurate in indicating impending danger of rollover, on the rollover warning platform, three LTRs have similar trends, while the proposed LTR performs better in predicting rollover.
Key concepts: Rollover (web design), Vehicle dynamics, Automotive engineering, Engineering, Suspension (topology), Computer science, Structural engineering, Mathematics