Performance evaluation and energy management of an automobile exhaust thermoelectric generator for ISG mild HEV application

Application of automobile exhaust thermoelectric generator (AETEG) has certain impact on the fuel economy of vehicle, and to further improve the fuel-saving performance of the traditional integrated starter and generator (ISG) based mild hybrid electric vehicle (HEV), an AETEG was developed and integrated into its powertrain system. Considering model predictive control (MPC) strategy has the advantages of high accuracy, strong reliability and wide application range, it was proposed to manage the energy distribution of ISG mild HEV equipped with AETEG. Firstly, the demand power of ISG mild HEV was predicted with Markov model. Then, a maximum power point tracking (MPPT) method of AETEG was applied to charge the batteries and propel the hybrid power system. Finally, the fuel consumption was treated as the objective function for the optimal torque distribution between internal combustion engine (ICE) and ISG based on a dynamic programming (DP) algorithm. Results demonstrate that the MPC-DP strategy with AETEG decreases the fuel consumption of ISG mild HEV by 5.63%, and ensures the maximum state of charge (SOC) drop-down of 22.67% and final SOC of 0.529 with same initial SOC value of 0.6. Contrast to the fuzzy logic control (FLC) and rule-based energy management strategy (REMS) applied under a composite driving cycle, the proposed MPC-DP method has obvious advantage in SOC stability and dynamic performance, the emission is decreased by at least 2.3%, and the average fuel economy is improved by 6.25% and 7.53%, respectively.