Multiobjective Optimisation and Active Control of Bogie Suspension

Railways provide fast, safe, clean, and cheap transportation service. The cost efficiency inrailway operations can be scrutinized from different perspectives. Here, passenger ride comfort,wheel/rail contact wear, and safety (in particular running stability, track shift force, and risk ofderailment) are considered as objective functions introduced to evaluate the dynamics behaviourof railway vehicles. Running speed also plays a key role in cost efficiency of railway operations.Higher speeds shorten journey time and make railways more competitive with other types oftransportation systems. However, this might increase wear and deteriorate ride comfort andsafety. To improve the performance in railway operations advanced designs and technologiesare developed during the past decades. Bogie primary and secondary suspension systems of highspeed trains can significantly affect the dynamics behaviour of the vehicle. Such componentsmight have conflicting effects on different objective functions. It is important to have theoptimum performance of suspension components. In this regard, one of the ultimate goals of thisthesis is to improve the vehicle performance from different points of views by studying passiveand active suspension systems and using multiobjective optimisation techniques to meetconflicting design requirements. Computational cost is one of the main challenges inmultidisciplinary design optimisation. The computational efforts for optimisation can besignificantly mitigated by narrowing down the number of input design parameters. Here, anefficient global sensitivity analysis is carried out to identify those suspension components thathave prominent influences on different objective functions. Based on the global sensitivityanalysis results obtained two multiobjective optimisation problems are formulated and solved.First, multiobjective optimisation of bogie suspension components with respect to safety toimprove running speed on curves. Second problem is to reduce wear and improve ride comfortwhen the vehicle is operating with the enhanced speeds. Consequently, the vehicle runs secureand faster with higher ride comfort and less wear by means of the two optimisation problemssolved. The optimisations are carried out using the genetic algorithm. In the case of safetyoptimisation problem, semi active control strategies are also applied using magnetorheologicaldampers and the effects on the dynamics behaviour are explored. The robustness of the bogiesuspension Pareto optimised solutions against uncertainties in the design parameters is alsostudied. Active control technology is one of the main targets of this thesis. In this regard, a robustcontroller is designed using the H∞ control technique to stabilize the wheel set motion andimprove curving performance. The controller is robust against track irregularities. Finally, theactuator dynamics is considered and a compensation technique is applied to reduce the actuator’stime delay and improve the performance