He, YupingIslam, Md. Manjurul2013-05-092022-03-292013-05-092022-03-292013-04-01https://hdl.handle.net/10155/309Multi-trailer articulated heavy vehicles (MTAHVs) exhibit unstable motion modes at high speeds, including jack-knifing, trailer swing, and roll-over. These unstable motion modes may lead to fatal accidents. On the other hand, these vehicle combinations have poor maneuverability at low speeds. Of all contradictory design criteria of MTAHVs, the trade-off relationship between the maneuverability at low speeds and the lateral stability at high speeds is the most important and fundamental. This trade-off relationship has not been adequately addressed. The goal of this research is to address this trade-off relationship through the design optimization of MTAHVs with active safety systems. A parallel design optimization (PDO) method is developed and applied to the design of MTAHVs with integrated active safety systems, which involve active trailer steering (ATS) control, anti-roll (AR) control, differential braking (BD) control, and a variety of combinations of these three control strategies. To derive model-based controllers, a single-trailer articulated heavy vehicle (STAHV) model with 5 degrees of freedom (DOF) and a MTAHV model with 7 DOF are generated. The vehicle models are validated with those derived using a commercial software package, TruckSim, in order to examine their applicability for the design optimization of MTAHVs with active safety systems. The PDO method is implemented to perform the concurrent design of the plant (vehicle model) and controllers. To simulate the closed-loop testing maneuvers, a driver model is developed and it is used to drive the virtual vehicle following the prescribed path. Case studies indicate that the PDO method is effective for identifying desired design variables and predicting performance envelopes in the early design stages of MTAHVs with active safety systems.enMulti-trailer articulated heavy vehiclesActive safety systemsDesign optimizationActive trailer steeringHigh performance computingDissertation