Context. Space weather predictions are necessary to avoid damage caused by intense geomagnetic storms. Such strong storms are usually caused by a co-rotating interaction region (CIR) passing at Earth or by the arrival of strong coronal mass ejections (CMEs). To mitigate the damage, the effect of propagating CMEs in the solar wind must be estimated accurately at Earth and other locations. Modelling solar wind accurately is crucial for space weather predictions, as it is the medium for CME propagation. Aims. The Icarus heliospheric modelling tool is upgraded to handle dynamic inner heliospheric driving instead of using steady boundary conditions. The ideal magnetohydrodynamic (MHD) solver and the automated grid-adaptivity are adjusted to the latest MPI-AMRVAC version. This new combination allows us to model the solar heliosphere more accurately. Methods. The inner boundary conditions, prescribed at 0.1 AU for the heliospheric model, are updated time-dependently throughout the simulation. The coronal model (r < 0.1 AU) is computed repeatedly for selected magnetograms, and the r = 0.1 AU radial boundary prescription is provided to the heliospheric modelling tool. The particle sampling within MPI-AMRVAC is extended to handle stretched spherical grid information. It is well suited for tracing solar wind plasma conditions at the locations of planets and satellites in the heliosphere. Results. The solar wind obtained in the simulation is dynamic and shows significant variations throughout the evolution. When comparing the results with the observations, the dynamic solar wind results are more accurate than previous results obtained with purely steady boundary driving. The CMEs propagated through the dynamic solar wind background produce more similar signatures in the time-series data than in the steady solar wind. Conclusions. Dynamic boundary driving in Icarus results in a more self-consistent solar wind evolution in the inner heliosphere. The upgraded particle sampling allows for a very versatile sampling of the solution at the spatio-temporally varying locations of satellites. The obtained space weather modelling tool for dynamic solar wind and CME simulations is better suited for space weather forecasting than a steady solar wind model.