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Knowing how the dynamic and energy behaviors of different neuron classes interact is fundamental to understanding the mechanisms of excitability within them. In the auditory nerve fibers (ANFs), the excitability among neuron classes plays a crucial role in exploring three types of auditory fibers, which are high-, medium-, and low-spontaneous-rate (HSR, MSR, and LSR). This study maps the modified Morris-Lecar ( ML ) neuron into a potassium-transformed, dimensionless variant. This is called K⁺ML, which is comparable to the ML neuron in aspects of dynamical behaviors. The present investigation assesses how ion channel weighted scaling reshapes excitability, dynamics, and energy profiles. Employing the identical parameters, a sodium-centered scaling yields an equivalent dimensionless system too. Here, we apply the potassium form for physiological relevance. This work establishes the biophysical utility of these models for emulating the behavior of HSR, MSR, and LSR in ANFs. The K⁺ML model significantly raises the Class 3 threshold, requiring more intense and rapidly increasing inputs, which are consistent with phasic, selective onset auditory neurons. This difference is further clarified by codimension-one bifurcation analysis, which shows that Class 3 preserves a stable resting state over a wider range of input current, consistent with its higher spike-initiation threshold. However, both models maintain Class 1 and Class 2 thresholds and frequency-current curves. This dynamical behavior is also reflected in the energy structure, as a Hamiltonian analysis based on Helmholtz decomposition reveals an inversion between classes. K⁺ML allocates nontrivial cost to Class 3 events while halving mean energy for Classes 1 and 2 compared to ML . With a medium-band-filtered Chua oscillator drive, K⁺ML exhibits stronger spike frequency adaptation, bursting, and selective phase-space engagement in Classes 1 and 2 and can elicit Class 3 spiking where ML remains quiescent. Our findings demonstrate that potassium scaling induces functional changes beyond mere unit conversion. Our main results show that the model is capable of reproducing the existing experimental data recorded from HSR and MSR based on Class 1 and Class 2, respectively.