Abstract
The development of advanced driver assistance systems relies on an accurate estimation of the tire-road friction coefficient and cornering stiffness of the vehicle, which are closely linked to internal and external driving conditions. In this paper, an identification algorithm capable of simultaneously estimate the friction coefficient and cornering stiffness of the front and rear tires is pursued. A nonlinear adaptive law is proposed for the estimation of vehicle parameters under certain excitation conditions. It is shown that, by exploring the lateral dynamic of the vehicle, the convergence of the parameters to their true values can be guaranteed. A comprehensive study has been carried out in order to reveal the necessary conditions for convergence and observability of the parameters. Simulation results with a high fidelity full order Carsim model show a good performance of the proposed identification method.

Abstract
The loss of rotational inertia in the future power systems motivate the need to find new technical solutions for this challenge. Many solution have emerged in last years based on power converters with emulation of inertia. In this paper, we explore the concept of distributed virtual inertia (DVI) by investigating a new control method that use the common DC bus capacitors in the DC link of the converter as a buffer of energy to provide an equivalent mechanical inertial response. Using time-domain simulations with a detailed two-stage Photovoltaic (PV) inverter, we observe and discuss the benefits in the grid frequency.

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