  The energy extraction from quantum sources is a key task to develop new
quantum devices such as quantum batteries (QB). In this context, one of the
main figures of merit is the ergotropy, which measures the maximal amount of
energy (as work) that can be extracted from the quantum source by means of
unitary operations. One of the main issues to fully extract energy from the
quantum source is the assumption that any unitary operation can be done on the
system. This assumption, in general, fails in practice since the operations
that can be done are limited and depend on the quantum hardware (experimental
platform) one has available. In this work, we propose an approach to optimize
the extractable energy inspired by the variational quantum eigensolver (VQE)
algorithm. In this approach, we explicitly take into account a limited set of
unitaries by using the hardware efficient asatz (HEA) class of parameterized
quantum circuits. As a QB we use an one-dimensional spin chain described by a
family of paradigmatic first neighbor Hamiltonians such as the $XXX$,$XXZ$,
$XYZ$, $XX$, $XY$ and transverse Ising models. By building our parameterized
quantum circuits assuming that different types of connectivity may be available
depending on the quantum hardware, we numerically compare the efficiency of
work extraction for each model. Our results show that the best efficiency is
generally obtained with quantum circuits that have connectivity between first
neighbor spins.
