Conventional Powertrain Research Articles

Transferability Assessment of OBD-Related Calibration and Validation Activities from the Vehicle to HiL Applications

With the Euro 7 pollutant emission legislation currently under discussion, advanced and more efficient exhaust aftertreatment systems are being developed. The technologies required for these are leading to an increase in the number of components and control systems requiring diagnoses strategies under the on-board diagnostics (OBD) legislation. With concurrent shorter development times and significant reductions in budgets allocated to conventional powertrain development, challenges in the field of OBD calibration and verification are already rising sharply. In response to these challenges, hardware-in-the-loop (HiL) approaches have been successfully introduced to support and replace conventional development methods. The use of complex simulation models significantly improves the quality of calibrations while minimizing the number of required prototype vehicles and test resources, thus reducing development costs. This paper presents a feasibility study for moving OBD-related calibration and validation tasks from the vehicle to a HiL platform. In this context, the calibration and verification process of an active diagnostic for monitoring the condition of the three-way catalyst (TWC) and the oxygen sensors in the exhaust aftertreatment system is presented. It is shown that all relevant signals are simulated with sufficient accuracy to ensure a robust transfer from the vehicle to a HiL test bench. Special attention is given to the simulation of aged components and their influence on the emission behavior of the system. Furthermore, it is discussed that transferring OBD tasks from the vehicle to the HiL test bench could result in significant savings in development time and a reduction in the number of physical prototype vehicles and test resources required.

Synergies and Trade-Offs in Hybrid Propulsion Systems Through Physics-Based Electrical Component Modeling

Abstract Hybrid-electric propulsion is recognized as an enabling technology for reducing aviation's environmental impact. In this work, a serial/parallel hybrid configuration of a 19-passenger commuter aircraft is investigated. Two underwing-mounted turboprop engines are connected to electrical branches via generators. One rear fuselage-mounted electrically driven ducted fan is coupled with an electric motor and respective electrical branch. A battery system completes the selected architecture. Consistency in modeling accuracy of propulsion systems is aimed for by development of an integrated framework. A multipoint synthesis scheme for the gas turbine and electric fan is combined with physics-based analytical modeling for electrical components. Influence of turbomachinery and electrical power system design points on the integrated power system is examined. An opposing trend between electrical and conventional powertrain mass is driven by electric fan design power. Power system efficiency improvements in the order of 2% favor high-power electric fan designs. A trade-off in electrical power system mass and performance arises from oversizing of electrical components for load manipulation. Branch efficiency improvements of up to 3% imply potential to achieve battery mass reduction due to fewer transmission losses. A threshold system voltage of 1 kV, yielding 32% mass reduction of electrical branches and performance improvements of 1–2%, is identified. This work sets the foundation for interpreting mission-level electrification outcomes that are driven by interactions on the integrated power system. Areas of conflicting interests and synergistic opportunities are highlighted for optimal conceptual design of hybrid powertrains.

Numerical Energy Analysis of In-Wheel Motor Driven Autonomous Electric Vehicles

Autonomous electric vehicles are being widely studied nowadays as the future technology of ground transportation, while their conventional powertrain systems limit their energy efficiencies and may hinder their broad applications in future. Here we report a study on the energy consumption, efficiency improvement and greenhouse gas emissions of a mid-size autonomous electric vehicle driven by in-wheel motors, through the development of a numerical energy model, validated and implemented in a case study. The energy analysis was conducted under three driving conditions: flat road, upslope, and downslope driving, considering autonomous driving patterns, motor efficiency optimization and regenerative braking. The case study based on the baseline electric vehicle driving data in West Los Angeles showed that an in-wheel motor driven autonomous electric vehicle can save up to 17.5% of energy during the slope driving. Additionally, it can reduce around 5.5% greenhouse gas emissions annually in each state in the United States. Using the efficiency maps of a commercial in-wheel motor, the energy model and validated results in this study are in line with actual situations and can be used to support the future development of energy-efficient autonomous electric vehicles and sustainable energy transitions in ground transportation.

Design of Two Fuel Cell Buses for Public Transport According to Two Different Operating Scenarios: Urban and Motorway

<div>The transport sector is one of the major parties responsible for carbon dioxide (CO<sub>2</sub>) and pollutants emissions in Europe. For this reason, one of the main commitments of the European Commission is its decarbonization by 2035/2040. To achieve this target, during the last decades, different propulsion technologies were developed such as hybrid electric vehicles (HEVs), plug-in electric vehicles (PHEVs), and battery electric vehicles (BEV). The first two proposals can be considered as bridging technology between the internal combustion engine (ICE) and the BEV because they offer at the same time comparable performance as conventional powertrains and improved efficiency. However, both technologies are struggling with the tightening of pollutants and CO<sub>2</sub> limits. On the other hand, the BEV can offer zero emissions at the tailpipe, but it suffers from limited range capabilities and the lack of fast-charging infrastructures. Within this context, the fuel cell vehicle (FCV) appears as an interesting opportunity because it offers zero tailpipe emissions and equivalent refuelling time of the ICE. This article evaluates through mathematical simulations the performance of two fuel cell electric buses (FCEBs), which are supposed to work respectively in urban and highway driving conditions. The urban bus is equipped with a single fuel cell (FC) module of 85 kW-Net and an electric motor (EM) of 225 kW. The intercity bus is equipped with two FC modules with a total power of 170 kW-Net and two EMs of 225 kW each. A sensitivity to the battery capacity from 20 kWh to 40 kWh was performed for both FECBs. The power split between the FC module and the high-voltage battery was optimized with the Equivalent Consumption Minimization Strategy (ECMS). The two FCEBs were tested considering different portfolios of cycles: in the case of the urban bus in Braunschweig and the Standardized On-Road Test Cycles SORT1 and SORT2 were assumed as a reference, while cycles like the Highway Fuel Economy Test (HWFET), European Transient Cycle (ETC), and cruising at 100 km/h were assumed as reference for the intercity. Simulation results highlighted that the increase of battery capacity in the case of the urban bus from 20 kWh to 30 kWh reduces hydrogen (H<sub>2</sub>) consumption by 11% along the Braunschweig cycle. On the other hand, in the case of the intercity bus, the fuel consumption is less affected by the increase of capacity in the same range. In this case a reduction of 4.7% is estimated for the HWFET cycle, and it is less than 1% in the case of cruising conditions.</div>

Real Driving Cycle Simulation of a Hybrid Bus by Means of a Co-Simulation Tool for the Prediction of Performance and Emissions

This work is focused on the simulation of a complete hybrid bus vehicle model performing a real-world driving cycle. The simulation framework consists of a coupled co-simulation environment, where all the vehicle sub-system models are linked to achieve a real time exchange of input and output signals. In the vehicle model also the electric devices of the powertrain and accumulation system are included. This co-simulation platform is applied to investigate the hybridization of a 12-m city bus, performing a typical urban driving mission. A comparison between the conventional powertrain is performed against the hybridized version, to highlight the advantages and challenges. In particular, the novelty of this modeling approach is that the IC engine simulation does not rely on pre-processed look-up tables, but exploits a high-fidelity one-dimensional thermo-fluid dynamic model. However, it was necessary to develop a fast simulation methodology to exploit this predictive tool, achieving a low computational cost. The 1D engine model is first validated against the experimental engine map data available, showing a good model predictivity. Then the 1D engine model and the other models of the powertrain are coupled to the vehicle model, in order to follow the prescribed velocity profile of the driving cycle. The complete model is applied under different conditions, to evaluate the impact on performance and emissions and assess the simulation predictivity.

Case study on hybrid-electric aircraft designs enabled by an enhanced SUAVE version

Hybridization seems to be a promising way for regional aircraft to reduce the climate impact of aviation in its sector. On the one hand, fully-electric propulsion offers a too limited range while on the other hand, a conventional powertrain cannot offer enough reduction in emissions. In this paper, a case study on hybrid-electric aircraft is performed enabled by an enhanced SUAVE version. A variation on several parameters is carried out for one exemplary hybrid-electric architecture: battery technology level, energy management strategies, hybridization of installed power, cruise speed and altitude. From this study a baseline design, focused mainly on environmental aspects, is selected. The impact of NOX emissions is improved by 83 % compared to the ATR 42, while CO2 has a 5 % benefit without accounting for the net-effect of sustainable aviation fuels which is not part of this study.

Creepage Distance Estimation of Hairpin Stators Using 3D Feature Extraction

The increasing demand for electric drives challenges conventional powertrain designs and requires new technologies to increase production efficiency. Hairpin stator manufacturing technology enables full automation, and quality control within the process is particularly important for increasing the process capacity, avoiding rejects and for safety-related aspects. Due to the complex, free-form geometries of hairpin stators and the required short inspection times, inline reconstruction and accurate quantification of relevant features is of particular importance. In this study, we propose a novel method to estimate the creepage distance, a feature that is crucial regarding the safety standards of hairpin stators and that could be determined neither automatically nor accurately until now. The data acquisition is based on fringe projection profilometry and a robot positioning system for a highly complete surface reconstruction. After alignment, the wire pairs are density-based clustered so that computations can be parallelized for each cluster, and an analysis of partial geometries is enabled. In several further steps, stripping edges are segmented automatically using a novel approach of spatially asymmetric windowed local surface normal variation, and the creepage distances are subsequently estimated using a geodesic path algorithm. Finally, the approach is examined and discussed for an entire stator, and a methodology is presented that enables the identification of implausible estimated creepage distances.

Impact of powertrain electrification on the overall CO2 emissions of intercity public bus transport: Tenerife Island test case

The adoption of plug-in electric buses are seen as a promising alternative to reduce greenhouse gas (GHG) emissions in the public transport system. Although from an operational point of view this type of vehicles are zero-emissions, the upstream phase contribution can be considerably high in regions with high carbon grid intensities.This paper presents a simulation study to evaluate the energy consumption and the corresponding well-to-wheels (WTW) CO2 emissions of conventional diesel, parallel hybrid and battery electric buses. The test case is the island of Tenerife, an isolated power system highly dependent on fossil-fuels for power generation. Validated models of the aforementioned propulsion architectures were simulated over five representative cycles, covering city and intercity lines with noticeable differences in terms of driving behaviour, distance and gradient. Although battery electric buses present energy consumption reductions of 70% compared to conventional powertrains, the large carbon grid intensity of the island has a negative effect on their potential to reduce WTW CO2 emissions. The results evince that parallel hybrids provide the largest benefit to abate WTW CO2 emissions, reaching a reduction figure of 38% compared to its conventional diesel counterpart.

Prospects of Controlled Auto-Ignition Based Thermal Propulsion Units for Modern Gasoline Vehicles

Gasoline engines employing the spatially distributed auto-ignition combustion mode, known as controlled auto-ignition (CAI), are a prospective technology for significantly improving engine efficiency and reducing emissions. This review paper provides an overview of developments in various gasoline CAI technologies and discusses their attendant strengths and weaknesses. Hybrid propulsion systems powered by high-efficiency gasoline CAI engines can provide a low-carbon pathway for mobility sector decarbonisation. Therefore, this paper focuses on the challenges and opportunities of CAI implementation, especially for electrified powertrains. Different control actuators that can extend the CAI operating range are discussed, and opportunities for synergistic operation between thermal and electric components of hybridised powertrains are identified. Such synergies can remove impediments in the way of CAI system adoption and can, thus, support CAI adoption and maximise efficiency gains from its implementation. The prospects of supporting CAI combustion for different powertrain electrification levels, hybrid architectures, engine size, and energy management systems are discussed. Load levelling offered by electrified powertrains through CAI-favouring energy management strategies has the potential to substantially relax the operating point requirements for CAI-based thermal propulsion units and to remove the need for expensive actuators. The highly flexible spark-assisted partially premixed compression ignition hybrid mode (SACI-PPCI) emerges as a promising CAI strategy for conventional powertrains, and the moderately flexible spark-assisted compression ignition (SACI) configuration can be a cost-effective thermal propulsion mode for electrified powertrains.

Numerical Evaluation of Fuel Consumption and Transient Emissions of Different Hybrid Topologies for Two-Wheeler Application

<div>In Asian countries, small two-wheelers form a major share of the automobile segment and contribute significantly to carbon dioxide (CO<sub>2</sub>) emissions. Hybrid drives, though not widely applied in two-wheelers, can reduce fuel consumption and CO<sub>2</sub> emissions. In this work three hybrid topologies, viz., P2 (electric motor placed between engine and transmission), P3 (electric motor placed between transmission and final drive), and power-split concepts (with planetary gear-train) have been modeled in Simulink, and their fuel consumption and emissions under the World Motorcycle Test Cycle (WMTC) have been evaluated. A physics-based model for the Continuously Variable Transmission (CVT) was used which is capable of predicting its transient characteristics. A map-based fuel consumption model and a Neural Network (NN)-based transient emission model were used for the engine. The NN-based transient emission model avoids the need to model the air path and fuel path in transient conditions, which is time consuming. The fueling characteristics of the Engine Control Unit (ECU) in transients need not be known if an NN model is built and tuned with sufficient experimental data. Several transient experiments were performed with speed-load profiles similar to the WMTC for tuning the NN emission models. Simulation results show that the P2 hybrid, P3 hybrid, and power-split drives have fuel economy benefits of about 27%, 37%, and 49%, respectively, compared to the conventional powertrain. However, nitrogen oxides (NOx) emissions are much higher for the hybrid powertrains due to the operation of the engine at higher load ranges for efficiency but are still within the prevailing BS6 Indian emission limits. A significant portion of the wheel energy input can be recovered through efficient regenerative braking in the WMTC. This will be even more significant under peak traffic city driving conditions. The belt losses in the CVT significantly reduce the potential benefits of the hybrid powertrain, and hence, an efficient transmission to replace it will be beneficial.</div>

Design and Reliability Analysis of a Series/Parallel Hybrid System with a Rotary Engine for Safer Ultralight Aviation

The conventional powertrain for ultralight aviation consists of a fixed pitch propeller connected to an internal combustion engine (ICE). Since ICEs have a limited thermal efficiency (<40%), new and more efficient powerplant configurations have recently been proposed in the scientific literature by adopting hybrid electric solutions. Hybridization has the additional benefit of increased safety thanks to redundancy. This is a very important issue in ultralight aviation, where a high percentage of accidents are caused by engine failure. In a previous investigation, the authors proposed the design of a series/parallel hybrid electric power system to increase safety and optimize fuel economy by controlling the engine working points during flight. A new powertrain, derived from an automotive Honda i-MMD system, is analyzed in this study and a reliability analysis is performed to underline the improved safety obtained with the proposed system.

Numerical Investigation of a Fuel Cell-Powered Agricultural Tractor

In recent years, growing awareness about environmental issues is pushing humankind to explore innovative technologies to reduce the anthropogenic sources of pollutants. Among these sources, internal combustion engines in non-road mobile machinery (NRMM), such as agricultural tractors, are one of the most important. The aim of this work is to explore the possibility of replacing the conventional diesel engine with an electric powertrain powered by a hybrid storage system, consisting of a small battery pack and a fuel-cell system. The battery pack (BP) is necessary to help the fuel cell manage sudden peaks in power demands. Numerical models of the conventional powertrain and a fuel-cell tractor were carried out. To compare the two powertrains, work cycles derived from data collected during real operative conditions were exploited and simulated. For the fuel-cell tractor, a control strategy to split the electric power between the battery pack and the fuel cell was explored. The powertrains were compared in terms of greenhouse gas emissions (GHG) according to well-to-wheel (WTW) equivalent CO2 emission factors available in the literature. Considering the actual state-of-the-art hydrogen production methods, the simulation results showed that the fuel-cell/battery powertrain was able to accomplish the tasks with a reduction of about 50% of the equivalent CO2 emissions compared to traditional diesel-powered vehicles.

Complex Evaluation of Heavy-Duty Truck Hybridization and Electrification Options

Abstract Parallel hybrid electric vehicle (HEV) powertrain topologies are easily applicable on an existing conventional powertrain, and are frequently used in passenger vehicles, with a goal to reduce the overall fleet CO2 emissions, either with mild, full, or plug-in capability. However, for the heavy-duty trucks, the powertrain electrification progresses more slowly. Therefore, the goal of this paper is to evaluate three different hybridization options, together with two electrification options, in comparison with conventional powertrain combined with 5.9 L 6-cylinder diesel internal combustion engine in a heavy-duty 7.5-ton application. All vehicle variants are evaluated in eight vehicle driving cycles replicating different heavy-duty use-cases at different cargo levels, also considering the economical aspect of these different electrification options, calculating the payback periods for each powertrain option. The energy management control strategy, that determines the power split between the ICE and electric motor for HEV variants is an optimal one, based on Pontryagin’s Minimum Principle. All models are programmed in-house in Python 3.9.0.

Heavy Multi-Articulated Vehicles with Electric and Hybrid Power Trains for Road Freight Activity: An Australian Context

The electrification of vehicles from the automotive and public transport industries can reduce harmful emissions if implemented correctly, but there is little evidence of whether the electrification of heavy freight transportation vehicles (HFTVs), such as multi-articulated vehicles, used in the freight industry could see the same benefits. This work studied heavy multi-articulated freight vehicles and developed a comparative analysis between electric and conventional diesel power trains to reduce their total emissions. Real-world drive cycle data were obtained from a heavy multi-articulated freight vehicle operating around Melbourne, Australia, with a gross combination mass (GCM) of up to 66,000 kg. Numerical models of the case study freight vehicle were then simulated with diesel, through-the-road parallel (TTRP) hybrid and electric power trains over the five different drive cycles with fuel and energy consumption results quantified. Battery weights were added on top of the real-world operating GCMs to assure the operational payload did not have to be reduced to accommodate the addition of electric power trains. The fuel and energy consumptions were then used to estimate the real-world emissions and compared. The results showed a positive reduction in tailpipe emissions, but total greenhouse emission was worse for operation in Melbourne if batteries were charged off the grid. However, if Melbourne can move towards more renewable energy and change its emission factor for generating electricity down to 0.49 kg CO2-e/kWh, a strong decarbonization could be possible for the Australian road freight industry and could help meet emission reduction targets set out in the 2015 Paris Agreement.

Quantifying the real-world CO2 emissions and energy consumption of modern plug-in hybrid vehicles

Plug-in Hybrid Electric Vehicles (PHEV) can be classified as low CO 2 emissions vehicles in Europe if they emit no more than 50 g/km, and are viewed as favourable transitional technology for road transport electrification. Some recent studies challenge their effectiveness in reducing CO 2 emissions in real-world conditions. This study tested four Euro 6 PHEVs, both in the laboratory and on the road, for CO 2 emissions and energy consumption. The experimental results show that PHEVs in-use CO 2 emissions can range from 0 to 6 times the official type-approval CO 2 value. The results were analysed to derive relevant operation models and emission factors and benchmark their in-use performance with respect to the officially declared consumption values. A three-dimensional CO 2 emissions model is proposed based on charge level and average trip speed or wheel energy. When considering different users' charging practices and representative real-world conditions, PHEVs in-use CO 2 emissions are 1.5–2 times the official type-approval CO 2 value. Although the real-world emissions of plug-in hybrids appear to increase compared to the official values, they generally remain lower than conventional powertrains. The single-modelling element approach presented offers a novel, robust, and simple to implement way to include PHEVs in planning exercises, emissions calculation models to support national and regional inventories, lifecycle emissions estimates, and fleet-wide emissions monitoring tools.

Artificial Intelligence-Based Machine Learning toward the Solution of Climate-Friendly Hydrogen Fuel Cell Electric Vehicles

The rapid conversion of conventional powertrain technologies to climate-neutral new energy vehicles requires the ramping of electrification. The popularity of fuel cell electric vehicles with improved fuel economy has raised great attention for many years. Their use of green hydrogen is proposed to be a promising clean way to fill the energy gap and maintain a zero-emission ecosystem. Their complex architecture is influenced by complex multiphysics interactions, driving patterns, and environmental conditions that put a multitude of power requirements and boundary conditions around the vehicle subsystems, including the fuel cell system, the electric motor, battery, and the vehicle itself. Understanding its optimal fuel economy requires a systematic assessment of these interactions. Artificial intelligence-based machine learning methods have been emerging technologies showing great potential for accelerated data analysis and aid in a thorough understanding of complex systems. The present study investigates the fuel economy peaks during an NEDC in fuel cell electric vehicles. An innovative approach combining traditional multiphysics analyses, design of experiments, and machine learning is an effective blend for accelerated data supply and analysis that accurately predicts the fuel consumption peaks in fuel cell electric vehicles. The trained and validated models show very accurate results with less than 1% error.

Technology selection for holistic analysis of hybrid-electric commuter aircraft

Electric powertrains have different characteristics than conventional powertrains with combustion engines and require unconventional aircraft designs to evolve their full potential. Therefore, this paper describes a method to identify potential aircraft designs with electrified powertrains. Promising technology options in the fields of powertrain architecture, aerodynamic interactions, onboard systems and operating strategies were collected by the project partners of the LuFo project GNOSIS. The effect of the technology options on a commuter aircraft was evaluated in terms of global emissions (hbox {CO}_{2}), local emissions (text {NO}_{text {X}} and noise) and operating costs. The evaluation considers an entry into service in 2025 and 2050 and is based on the reference aircraft Beechcraft 1900D. Literature review and simplified calculations enabled the evaluation of the aerodynamic interactions, systems and operating strategies. A preliminary aircraft design tool assessed the different powertrain architectures by introducing the two parameters ’power hybridization’ and ’power split’. Afterwards, compatible technology options were compiled into technology baskets and ranked using the shortest euclidean distance to the ideal solution and the farthest euclidean distance to the worst solution (Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method). An analysis of the CS 23 regulations leads to a high-wing design and excluded the partial turbo-electric powertrain architecture with the gas turbine in the aircraft tail. For 2025, a partial turbo-electric powertrain with two additional electric driven wingtip propellers was selected. A serial hybrid powertrain, which uses a gas turbine or fuel cell in combination with a battery, powers distributed electric propulsors at the wing leading edge in 2050. In both scenarios, the aircraft design includes an electric environmental control system, an electric driven landing gear and electro-hydraulic actuators for the primary flight control and landing gear.

Lean Burn Flame Kernel Characterization for Different Spark Plug Designs and Orientations in an Optical GDI Engine

Lean burn spark ignition (SI) engines represent an effective solution for improving fuel economy and reducing exhaust emissions and can be implemented both in conventional and hybrid powertrains. On the other hand, lean operation increases cyclic variability with negative impact on power output, engine efficiency, roughness, and operating stability. Although this phenomenon has been widely investigated, the effects of flow field on the inception and development of flames in direct injection spark ignition (DISI) engines under lean burn conditions is not yet completely understood. In particular, the effect of spark plug geometry and electrode orientation with respect to tumble motion has been minimally investigated. For these reasons, two different spark-plug geometries (i.e., single- and double-ground electrode) and three different orientations (i.e., cross-, counter-, and uni-flow with respect to the direction of tumble motion) were investigated in an optically accessible DISI engine for understanding their influence on the initial phase of combustion. The relative air–fuel ratio (AFRrel) was changed from stoichiometric to lean burn (1.00 to 1.30) for different spark timings around the maximum brake torque setting at fixed engine speed (2000 rpm). An image processing procedure was developed for evaluating the morphological parameters of flame kernels and studying the effects of spark plug design on engine operating stability. With a focus on the correlation between the position where ignition occurs with the subsequent locations of the flame kernel during the first phases of the combustion process, the analysis allowed the gathering of a better understanding of the influence that the electrodes’ geometries and orientation can have on the first stages of combustion development.

An empirical analysis of electric vehicle cost trends: A case study in Germany

This study conducts a learning rate analysis on electric vehicle retail prices in Germany between 2015 and 2020 to predict the point of purchase price parity between electric cars and comparable conventional vehicles in different market segments. In small cars, a learning rate of 23% was found. For mid-sized cars, the rate of cost decline was 29%. A learning rate of 24% was observed in the luxury segment. Based on these results, it was found that luxury BEVs would reach price parity by the year 2023, and that midsized vehicle would follow by 2026. For small cars, the results indicate that price parity will not be achieved before the year 2030. The price parity results are complemented with an evaluation of the present and future total cost of ownership of electric and conventional cars. The analysis found that in 2020, mid-size and large electric vehicles were already close to price parity with conventional cars, even before subsidies provided by the German government. Small electric cars still required significant subsidies to be cost-competitive, however. The sensitivity of the analysis results to certain key parameters was evaluated, including the standard error of the learning rates, expected global BEV production in future years, the cost of conventional powertrains, and the effect of government subsidies on the ownership cost, and the duration of the vehicle ownership period. Overall, the results suggest that while the cost gap in larger cars will be closed around the middle of the decade, a higher rate of technological innovation is needed to make small BEVs cost-competitive with gasoline cars before the year 2030.

Development of Optimization Based Control Strategy for P2 Hybrid Electric Vehicle including Transient Characteristics of Engine

Models based on steady-state maps estimate fuel consumption to be 2–8% lower than real experimental measured values. This is due to the fact that during transient phases, the engine consumes more fuel than in steady phases. Some literature has addressed the conventional vehicle engine model that improves fuel consumption estimation’s accuracy during the transient state. However, the characteristics of the engine in the scope of hybrid electric vehicles (HEVs) with an integrated control strategy is yet to be covered. The controller is designed to minimize engine operation in the transient phase to enhance energy savings. In this paper, the correlation between fuel enrichment in transient and steady-state fuel estimation is established as transient correction factor (TCF). Its explanatory variable was the engine torque change rate. This paper describes the influence of engine transient characteristics on the fuel consumption of a mild HEV. The work attempts to improve the fuel economy of the HEV by introducing a penalty factor in the controller to optimize the use of the engine in transient regimes. A backward vehicle model was developed for a production vehicle with a conventional powertrain and validated experimentally using data available online. The corresponding hybrid vehicle model was developed by integrating the electric motor and battery components with the conventional vehicle model. A P2 off-axis configuration was chosen to this end as the HEV architecture. A conventional equivalent consumption minimization strategy (ECMS) was used to split the torque request between the engine and the electric motor. This control strategy was modified with TCF to penalize the engine torque change rate. The results of the simulation show that due to less transient operation of the engine, the fuel consumption was reduced from 923 g to 918 g under the US06 driving cycle. The fuel economy of the model has been simulated for UDDS and HW drive cycles too, and fuel consumption improved by 4.4 g and 3.2 g, respectively. It has been verified that by increasing the battery capacity twice (14s24p), the limitations imposed by the battery capacity can be minimized and the fuel usage can be reduced by 9 g in the UDDS cycle.