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Colloidal heat engines extract power out of a fluctuating bath bymanipulating a confined tracer. Considering a self-propelled tracer surroundedby a bath of passive colloids, we optimize the engine performances based on themaximum available power. Our approach relies on an adiabatic mean-fieldtreatment of the bath particles which reduces the many-body description into aneffective tracer dynamics. It leads us to reveal that, when operated atconstant activity, an engine can only produce less maximum power than itspassive counterpart. In contrast, the output power of an isothermal engine,operating with cyclic variations of the self-propulsion without any passiveequivalent, exhibits an optimum in terms of confinement and activity. Directnumerical simulations of the microscopic dynamics support the validity of theseresults even beyond the mean-field regime, with potential relevance to thedesign of experimental engines.

Extracting maximum power from active colloidal heat engines