Multi-objective vehicle optimization: Comparison of combustion engine, hybrid and electric powertrains

Abstract

The use of optimization techniques has been extensively adopted in vehicle design and with the increasing complexity of systems, especially with the introduction of new technologies, it plays an even more significant role. Market competition, stringent mandatory emission regulations and the need for a future sustainable mobility have raised questions over conventional vehicles and are pushing toward new cleaner and eco-friendly solutions. Fulfilling this target without sacrificing the other vehicle’s requirements leads to extremely challenging tasks for vehicle designers. The use of virtual prototyping emerges as a possible breakthrough allowing to rapidly assess the effect of design changes and the impact of new technologies. The study presented in this work provides a suitable approach to compare different vehicle powertrain architectures through optimization techniques and deploying model-based simulation to rapidly assess vehicle performances. The vehicle model is defined at the components level through scalable models obtained from based on detailed simulation. An optimal energy management is applied to the power sources and transmission gear shifting. The optimization technique consider the main design variables of the various components including vehicle chassis and extensively exploits the design space. The multi-objective optimization considers vehicle’s consumption, emission, range, longitudinal and lateral dynamics, costs and further performances to comprehensively assess the vehicle. The results allow to compare four different powertrain architectures: combustion engine vehicle, hybrid electric vehicle with parallel and series configuration, and battery electric vehicle. The results allows furthermore to identify technological limitations and conflicts among the different objectives. A critical analysis over the main design variables allows to identify the more suitable values and in particular, for combustion engine, gearbox and electric traction drive detailed comparisons are provided.

Ecodesigning and improving performance of plugin hybrid electric vehicle in rolling terrain through multi-criteria optimisation of powertrain

“…The total cost of ownership (TCO) analysis and the summary of model performance has been presented in table 15 and 16, respectively, for the three design solution points obtained from three surrogate assisted optimisation algorithms. The result in table 16, shows that the SAEA models reduce the total fuel cost by about 60 % over the ownership period or conventionally considered life of the vehicle in comparison to the base model. The emission values also reduced in comparison to the base model and here GRA based SAEA solution produces better result while in terms of gradeability the MTOPSIS based SAEA is the best solution which can be observed in table 16.…”

“…The result in table 16, shows that the SAEA models reduce the total fuel cost by about 60 % over the ownership period or conventionally considered life of the vehicle in comparison to the base model. The emission values also reduced in comparison to the base model and here GRA based SAEA solution produces better result while in terms of gradeability the MTOPSIS based SAEA is the best solution which can be observed in table 16. In the final weighted sum approach for best design selection, it has been observed, in figure 13, the MTOPSIS based SAEA produces the best result in the wide range of variation weight value.…”

“…For example, Millo, et al, 2017 converts the multiple objectives into a single cost function and the CO 2 emission got reduced by 23% and the operating costs by 26% 15 . Vehicle cost, efficiency, emission, light-weighting and vehicle life as objective is considered in another similar work 16 . Geng, et al, 2018 searched best PHEV transmission configuration which improves fuel economy (FE) around 4% to 10% for three driving cycles while minimising the consumption of fossil fuel and total energy 17 .…”

Design of an Aftermarket Hybridization Kit: Reducing Costs and Emissions Considering a Local Driving Cycle

“…Thus, the throttle pedal signal is acquired and the PMC splits the requested traction torque T eng according to the P E factor (defined in the optimization problem). The engine torque T eng and torque of the electric motors T el are defined by Equations (6) and (7) respectively, according to the engine inertia I e (kgm 2 ); gearbox and differential gear ratios N t and N d ; inertia I t (kgm 2 ) and I d (kgm 2 ); the frontal and real wheels inertia I w f (kgm 2 ) and I wr (kgm 2 ); and the overall powertrain efficiency η td .…”

“…Plugin hybrid electric vehicles are driven by electric motors (EMs) and internal combustion engines (ICE) and can be connected to the grid [5]. They are one of the solutions for mitigating local emissions [6] and absorbing fuel and electric energy price instabilities.…”