Optimal Energy Management for a Mild Hybrid Vehicle With Electric and Hybrid Engine Boosting Systems

Development of a computer platform for visualisation and simulation of vehicular DC distribution systems

“…From the software design point of view, simulation capabilities can be leveraged by considering recent related academic contributions. Between these we have optimal hybrid energy management [63], low‐cost 48 V switched reluctance drive [64], DC/DC converter architectures [65, 66], hybridisation degree levels [67], motor‐inverter power module for electric compressor [68], modelling and validation of lithium‐ion battery packs [69], and integrated converters for mild hybrid starter‐generators [70, 71].…”

“…By doing so, no insulation upgrades are required and the fuel consumption is reduced by decreasing the engine idling time when the vehicle is stopping, braking, or cruising. Moreover, the electric motor can guide the ICE to efficient operating points and even accomplish partial regenerative braking [63]. Given these benefits, automakers are showing high interest in mild hybrid technology.…”

Power Split Supercharging: A Mild Hybrid Approach to Boost Fuel Economy

“…A 1.2 kWh lithium ion battery is assumed for the vehicle. An Open Circuit Voltage with a Resistance (OCV-R) is used to model the battery and compute its state of charge dynamics detailed in [13]…”

“…The global fuel consumption minimization problem for a vehicle equipped with a PSS was formulated and solved using Dynamic Programming (DP) by the authors elsewhere [13,17]. In this work the online energy management system is compared to DP results to determine the sub optimality of the solution, hence only a brief summary of the DP formulation is provided.…”

“…The global fuel consumption minimization for a hybrid electric vehicle equipped with a power split supercharger under a charge sustaining constraint was previously formulated and solved using Dynamic Programming (DP) by the authors [13] and a simple online energy management system based on Equivalent Consumption Minimization Strategy (ECMS) was also previously presented [14] and was tested in simulation. This work extends our previous efforts by developing an Adaptive-ECMS (A-ECMS) and documenting the fuel economy benefits of the PSS through advanced hardware-in-the-loop (HIL) experiments.…”