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  • 1.
    Bhat, Sriharsha
    et al.
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics.
    Davari, Mohammad Mehdi
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics. KTH, School of Engineering Sciences (SCI), Centres, VinnExcellence Center for ECO2 Vehicle design.
    Nybacka, Mikael
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Vehicle Dynamics. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Study on energy loss due to cornering resistance in over-actuated electric vehicles using optimal control2017In: SAE International Journal of Vehicle Dynamics, Stability, and NVH - V126-10, 2017Conference paper (Refereed)
    Abstract [en]

    As vehicles become electrified and more intelligent in terms of sensing, actuation and processing; a number of interesting possibilities arise in controlling vehicle dynamics and driving behavior. Over-actuation with in- wheel motors, all wheel steering and active camber is one such possibility, which facilitate the control strategies that push boundaries in energy consumption and safety. Optimal control can be used to investigate the best combinations of control inputs to an over-actuated system. This paper shows how an optimal control problem can be formulated and solved for an over-actuated vehicle case, and highlights the translation of this optimal solution to a real-world scenario, enabling intelligent means to improve vehicle efficiency. This paper gives an insight into the Dynamic Programming (DP) as an offline optimal control method that guarantees the global optimum. Therefore the optimal control allocation to minimize an objective function and simultaneously fulfill the defined constraints can be achieved. As a case study the effect of over-actuation on the cornering resistance were investigated in two different maneuvers i.e. step steer and sine with dwell, where in both cases the vehicle assumes to be in steady state situation. In this work the cornering resistance is the main objective function and maintaining the reference trajectory is the constraint which should be fulfilled. A parameter study is conducted on the benefits of over-actuation, and depending on the type of over-actuation about 15% and 50% reduction in cornering resistance were observed during step steer and sine with dwell maneuver respectively. From a second parameter study that focused on COG position from a safety perspective, it is more beneficial for the vehicle to be designed to under-steer than over-steer. Finally, a method is described to translate the offline optimal results to vehicle implementable controllers in the form of both feed-through lookup-tables and rule-based feed-forward control.

  • 2.
    Bhat, Sriharsha
    et al.
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Stenius, Ivan
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Hydrobatics: A Review of Trends, Challenges and Opportunities for Efficient and Agile Underactuated AUVs2018In: AUV 2018 - 2018 IEEE/OES Autonomous Underwater Vehicle Workshop, Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2018Conference paper (Refereed)
    Abstract [en]

    Hydrobatics refers to agile maneuvering of under-water vehicles just like aerobatics represents agile maneuvering of aerial vehicles. Performance trade-offs between flight and hover style autonomous underwater vehicles (AUVs) means that either maneuverability or range is compromised. Hydrobatic capabilities in flight style AUVs can bridge this gap and lead to more efficient and agile vehicles; thereby encouraging disruptive designs. As this is a relatively new area of research with very limited published research work, the focus of this paper is to present a multidisciplinary literature review to provide a path forward for further research. Relevant impact areas in ocean production, environmental sensing and security are discussed. Technical challenges are described in underactuated control and flight dynamics modeling. Synergies and opportunities are explored with aerospace engineering, robotics and artificial intelligence. As a part of this study, a simulation and verification framework is suggested and ongoing work is presented.

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