The goal of this research is to achieve close to real-time dynamics performance for allowing auto-pilot in-the-loop testing of unmanned ground vehicles (UGV) for urban as well as off-road scenarios. The overall vehicle dynamics performance is governed by the multibody dynamics model for the vehicle, the wheel/terrain interaction dynamics and the onboard control system. The topic of this paper is the development of computationally efficient and accurate dynamics model for ground vehicles with complex suspension dynamics. A challenge is that typical vehicle suspensions involve closed-chain loops which require expensive DAE integration techniques. In this paper, we illustrate the use the alternative constraint embedding technique to reduce the cost and improve the accuracy of the dynamics model for the vehicle.

The paper describes the design and multibody dynamic analysis of a mechanically interconnected suspension, as applied to a small off-road vehicle. Interconnected suspensions use some sort of connection between the axles of a vehicle in order improve ride quality or vehicle handling. In principle, the connection may be hydraulic, pneumatic, or mechanical, but for installation in a typical passenger car, a mechanical connection would likely be impractical due to weight and complexity. In this paper, the vehicle in question is the University of Windsor SAE Baja off-road competition vehicle, and novel mechanical design is proposed. A multibody dynamic analysis is performed on the proposed design using the EoM open source multibody software developed by theUniversity ofWindsorVehicle Dynamics and Control research group in order to assess any potential performance improvements.

The purpose of the present research relates to the sensitivity analysis of road vehicle comfort and handling performances with respect to suspension technological parameters. The envisaged suspension being of semi-active nature, this implies first to consider an hybrid modeling approach consisting of a 3D multibody model of the full car - an Audi A6 in our case - coupled with the electro-hydraulic model of the suspension dampers. Concerning parameter sensitivitie, the goal is to capture them for themselves - and not necessarily for optimization purpose - because their knowledge is of a great interest for the damper manufacturer.

An important issue of the research is to consider objective functions which are based on complete time integrations along a given trajectory, the goal being - for instance - to quantify the sensitivity of the carbody rms acceleration (comfort) or of the vehicle overturning character (handling) with respect to suspension parameters. On one hand, the accuracy of the various partial derivatives computation can be greatly enhanced thanks to the symbolic capabilities of our ROBOTRAN multibody program. On the other hand, the computational efficiency of the process also takes advantage of the recursive formulation of the multibody equations of motion which must be time integrated with respect to both the generalized coordinates and their partial derivatives in case of the so-called direct method underlying sensitivity analysis.

Despite the ever-increasing computational power of modern processors, the reduction of complex multibody dynamic models remains an important topic of investigation, particularly for design optimization, sensitivity analysis, parameter identification, and controller tuning tasks, which can require hundreds or thousands of simulations. In this work, we first develop a high-fidelity model of a production sports utility vehicle in Adams/Car. Single-link equivalent kinematic quarter-car (SLEKQ, pronounced “sleek”) models for the front and rear suspensions are then developed in MapleSim. To avoid the computational complexity associated with introducing bushings or kinematic loops, all suspension linkages are lumped into a single unsprung mass at each corner of the vehicle. The SLEKQ models are designed to replicate the kinematic behaviour of a full suspension model using lookup tables or polynomial functions, which are obtained from the high-fidelity Adams model in this work. The predictive capability of each SLEKQ model relies on the use of appropriate parameters for the nonlinear spring and damper, which include the stiffness and damping contributions of the bushings, and the unsprung mass. Homotopy optimization is used to identify the parameters that minimize the difference between the responses of the Adams and MapleSim models. Finally, the SLEKQ models are assembled to construct a reduced 10-degree-of-freedom model of the full vehicle, the dynamic performance of which is validated against that of the high-fidelity Adams model using four-post heave and pitch tests.

Active suspension systems ease the conflict between comfort and handling. This requires the use of suitable actuators that in turn need to be efficiently controlled. This paper proposes a model-based control approach for a nonlinear suspension actuator. Firstly the concept is derived in the linear framework in order to simplify the synthesis and analysis phase. There a linear model of the actuator is proposed and discussed. Further, this design phase includes a comparison between model-free PID controllers and a newly proposed two-degree-of-freedom controller which allows one to shape reference and disturbance responses separately. Subsequently, the two-degree-of-freedom controller, which proves to be superior, is adapted to the nonlinear framework by considering a linear parameter varying representation of the nonlinear plant. Finally, the nonlinear controller is implemented in a test car confirming the concept applicability to real hardware.