A Modeling-Based Predictive Regenerative Braking Strategy for a Parallel P2 Hybrid Electric Vehicle

Regenerative braking control in a hybrid electric vehicle must be evaluated at both the brake and powertrain levels, and additional recovered energy does not necessarily imply lower fuel consumption. This study examines a preview-aware C3 controller for a midsize parallel P2 hybrid electric vehicle against a causal, state-of-power-constrained C2 controller. C3 changes the desired regenerative torque share during braking and modifies the SOC target and power allocation before predicted deceleration. The controllers were evaluated on FTP-75, WLTP Class 3b and US06 using 100 matched realizations of six uncertain factors per cycle (300 C2–C3 pairs). Mean battery-recovered energy increased by 1.751%, 1.420% and 4.083%, while friction braking energy decreased by 5.100%, 4.393% and 11.842%, respectively. All 300 pairs favored C3 on the three braking metrics. Full-cycle factorial ablations attributed the nominal recovery gain primarily to the braking-torque allocation channel. SOC target preparation alone yielded negligible additional recovery at the tested initial SOC. With the stated algebraic terminal-SOC correction, mean fuel effects were −0.171%, −0.439% and +0.118%, respectively, where positive values indicate a reduction. Direct SOC-matched checks preserved the cycle-dependent sign, but the US06 advantage was only about 0.03–0.05%. Thus, the robust braking-energy benefit and the small, cycle-dependent fuel response arise from distinct control mechanisms. Improved recuperation alone does not establish a fuel-economy benefit.