  We analyse and improve the volume-penalty method, a simple and versatile way
to model objects in fluid flows. The volume-penalty method is a kind of
fictitious-domain method that approximates no-slip boundary conditions with
rapid linear damping inside the object. The method can then simulate complex,
moving objects in general numerical solvers without specialised algorithms or
boundary-conforming grids. Volume penalisation pays for this simplicity by
introducing an equation-level error, the $\textit{model error}$, that is
related to the damping time $\eta \ll 1$. While the model error has been proven
to vanish as the damping time tends to zero, previous work suggests convergence
at a slow rate of $\mathcal{O}(\eta^{1/2})$. The stiffness of the damping
implies conventional volume penalisation only achieves first order numerical
accuracy. We analyse the volume-penalty method using multiple-scales
matched-asymptotics with a signed-distance coordinate system valid for
arbitrary smooth geometries. We show the dominant model error stems from a
displacement length that is proportional to a Reynolds number $\text{Re}$
dependent boundary layer of size $\mathcal{O}(\eta^{1/2}\text{Re}^{-1/2})$. The
relative size of the displacement length and damping time leads to multiple
error regimes. Our key finding derives a simple smoothing prescription for the
damping that eliminates the displacement length and reduces the model error to
$\mathcal{O}(\eta)$ in all regimes. This translates to second order numerical
accuracy. We validate our findings in several comprehensive benchmark problems
and finally combine Richardson extrapolation of the model error with our
correction to further improve convergence to $\mathcal{O}(\eta^{2})$.
