Accurate battery state-of-charge (SOC) estimation is essential for off-grid energy systems, where power availability directly restricts autonomy and mission reliability. Traditional methods for battery modeling and estimation rely on high-precision instrumentation and extensive testing, which are impractical for embedded and resource-limited setups. The aim of this paper is to determine the measurement accuracy that is necessary to achieve practical SOC estimation. A 14S NMC prismatic battery pack made up of Samsung SDI 94 Ah cells was subjected to pulsed load conditions similar to those in mobile energy systems. The setup uses controlled current steps across a range of 5A to 100A and records voltage responses using various data acquisition systems of varying fidelity. The experiment varied pulse duration, amplitude, relaxation times, sampling rate, and bit width. Higher-fidelity acquisition improved repeatability and clarity of transient features. DCIR was consistently identified at ~4.6 mΩ (±0.2 mΩ across 20–100 A pulses). Simple measurement chains enabled the construction of first-order equivalent circuit models with time constants on the order of ~1–2 s, while slower polarization effects remained unresolved. Using these models, SOC estimation via an extended Kalman filter achieved <3–5% RMSE over the tested duty cycles when using ≥14-bit acquisition. Below this threshold, parameter extraction became inconsistent, with resistance estimates varying by >20% between identical pulses. An improvement of approximately 3 ENOB was achieved through oversampling and use of a 1 ppm voltage reference, reducing voltage noise to the sub-millivolt range (~0.5–1 mV) and enabling stable parameter identification at both 14- and 16-bit nominal resolution. Usable battery intelligence for off-grid energy systems can be achieved with minimal sensing infrastructure when the test design is appropriately constrained. This supports scalable integration of battery models in embedded energy systems and aligns with emerging requirements for deployable digital battery representations.