Gear shifting multi-objective optimization to improve vehicle performance, fuel consumption, and engine emissions

Eckert, Jony Javorski; Santiciolli, Fabio Mazzariol; Bertoti, Elvis; Costa, Eduardo dos Santos; Corrêa, Fernanda Cristina; Silva, Ludmila C. A.; Dedini, Franco Giuseppe

doi:10.1080/15397734.2017.1330156

Cited by 33 publications

(31 citation statements)

References 17 publications

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“…In this condition, the total engine output torque is transmitted to the gearbox. On the other hand, during the gear shifting process, the clutch disconnects the ICE from the gearbox (CPD = 0 to CPD = 100 mm) in 0.3 s. After the clutch fully opened (CPD = 100 mm), the gear ratio is changed in 0.2 s; then, the ICE is reconnected to the gearbox (CPD = 100 to CPD = 0 mm) in 0.5 s [32]. Therefore, the gearbox input torque T gb (Nm) is defined according to the rules presented in Equation (9) and the available traction torque at the vehicle frontal wheels T a f (Nm) is then defined by Equation (10).…”

Section: Ice System Restrictionsmentioning

confidence: 99%

“…These values correspond to the engine operation point, and are input to the ADVISOR TM fuel converter block, which defines the ICE fuel consumption F C (l) and the tailpipe emissions HC (g/km) NOx (g/km) and CO (g/km) according to the ICE maps shown in Figure 5. ADVISOR TM [47] is a free vehicular simulation tool that considers the ICE transient regimes, simulating the combustion heat and its influence in the catalyst efficiency that significantly changes the generated tailpipe emissions [32].…”

Section: Fuel Consumption and Emissionsmentioning

confidence: 99%

“…Finally, the simulation parameters related to the applied gear shifting strategy have to be defined; they significantly influence the energy management [60], the vehicle performance, the fuel consumption and the emissions [32,33]. The use of an adequate gear shifting strategy improves the gains reached by the vehicle hybridization, once the electric motors decrease the ICE torque demand, allowing for the anticipation of the upshifts, moving the engine to a lower fuel consumption/better efficiency operation point [34].…”

Section: Gear Shifting Strategymentioning

confidence: 99%

“…The hybridization kit was developed to be adapted to a conventional vehicle a manual gearbox; the most adequate gear will be shown to the driver by means of a user interface adapted to the vehicle. As in previous works [32,34,45], the gear shifting strategy is based on speed limits; in other words, when the vehicle reaches one of these limits, the gear will be changed to the next (upshift) or previous gear (downshift). In the simulation the shifting process is controlled by the vector V shift (Equation (27)) that contains the upshift speeds V u(i) (km/h) and the speed interval V D (km/h) used to define the downshift speeds 28).…”

Section: Gear Shifting Strategymentioning

confidence: 99%

“…The increase in the ICE warm-up period is amplified by the addition of the extra electric traction system, which supplies a parcel of the power demand and therefore decreases the ICE torque that can increase the generated emissions if the power split between ICE and EMs is not properly defined [31]. Modifications in the standard driving behavior, e.g., changing the gear shifting strategy, can decrease the ICE fuel consumption and emissions [32,33].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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For decades, drivers and fleet managers have been impacted by the instability of fuel prices, the need to save resources and the duty to meet and attain environmental regulations and certifications. Aiming to increase performance and efficiency and reduce emissions and mileage costs, plug-in electric vehicles (PHEVs) have been pointed out as a viable option, but there are gaps related to tools that could improve the numerous existing conventional vehicles. This study presents the design of an aftermarket hybridization kit that converts a vehicle originally driven by a combustion engine into a PHEV. To achieve this goal, an optimization was conducted with the objective of decreasing the cost (regarding fuel consumption and battery charging) to perform a local driving cycle, while attenuating the tailpipe emissions and reducing the battery mass. The torque curves of the electric motors, the battery capacity, the parameters for a gear shifting strategy and the parameters for a power split control were the design variables in the optimization process. This study used the Campinas driving cycle, which was experimentally obtained in a real-world driving scenario. The use of a local driving cycle to tune the design variables of an aftermarket optimization kit is important to achieve a customized product according to the selling location. Among the optimum solutions, the best trade-off configuration was able to decrease the mileage cost in 22.55%, and reduce the tailpipe emissions by 28.4% CO, 33.55% NOx and 19.11% HC, with the addition of a 137 kg battery.

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Section: Ice System Restrictionsmentioning

confidence: 99%

Section: Fuel Consumption and Emissionsmentioning

confidence: 99%

Section: Gear Shifting Strategymentioning

confidence: 99%

Section: Gear Shifting Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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An Optimization Approach for Improving Comprehensive Performance of PHET Based on Evolutionary Many‐Objective Optimization

Chai

Zhao

et al. 2022

Advcd Theory and Sims

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The parameter optimization coupled with the control strategy and target driving cycle directly affects the performance of vehicles. This paper proposes an optimization approach for a plug‐in hybrid electric truck (PHET), which considers comprehensive performances including fuel economy, emissions, vehicle drivability, safety, and dynamics. First, 10 initial design parameters are selected from powertrain components and a real‐time energy management strategy (EMS). Then, a definitive screening design (DSD) is proposed to simplify the design parameters. Finally, non‐dominated sorting genetic algorithm‐III (NSGA‐III) is proposed to solve a constrained many‐objective optimization problem with 9 objectives, and the design space is refined through a sensitivity analysis. Simulation results demonstrate that the proposed optimization approach can achieve significant improvements regarding both the comprehensive performances, power repartition, and system efficiency. The simulation is conducted both on Chinese Heavy‐Duty Commercial Vehicle Test Cycle (CHTC) and Urban Dynamometer Driving Schedule for Heavy‐Duty Vehicles (UDDSHDV). In addition, to guide a decision maker (DM) to make trade‐offs among many objectives, preferences are also incorporated into the solutions.

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Powertrain Optimization to Improve Vehicle Performance and Fuel Consumption

Eckert

Corrêa

Bertoti

et al. 2017

Multibody Mechatronic Systems

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Gear shifting multi-objective optimization to improve vehicle performance, fuel consumption, and engine emissions

Cited by 33 publications

References 17 publications

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

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

An Optimization Approach for Improving Comprehensive Performance of PHET Based on Evolutionary Many‐Objective Optimization

Powertrain Optimization to Improve Vehicle Performance and Fuel Consumption

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