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Increasingly stringent pollutant emission regulations and a customer demand for a high-fuel economy drive the modern automotive industry to hurriedly solve the problem of decarbonization and powertrain efficiency, leading R&D towards alternative powertrain solutions and fuels. Electrification, today, plays the biggest role in the topic, with Mild Hybrid Electrified Vehicles (MHEVs) being the most cost-effective architectures, displaying dominance in smaller markets such as Brazil. One of the biggest challenges for HEVs' development is the complexity of the hybrid control system, knowing when to actuate the electric machine, and the optimum power delivery, plus the gearshift schedule becomes a hard optimization problem that plays a key role in powertrain efficiency and cost savings for the customer. This paper proposes the implementation of a genetic algorithm (GA) as a machine learning-based control strategy to determine the torque split and the gear engaged for each driving condition of an MHEV operation, aiming to optimize fuel consumption. A quasi-static model of the vehicle was developed in Matlab/Simulink version 2022b, the virtual vehicle was then tested following the FTP75 and HWFET driving cycles. Simulation results indicate that the control decisions taken by the GA are qualitatively coherent for all operation conditions, and even quantitatively coherent in some cases, and that the software has the potential to be used as a control strategy outside the simulation environment, in future steps of development. [ABSTRACT FROM AUTHOR]

The transportation sector has the highest energy demand worldwide and bears the primary responsibility for CO2 emissions. Electromobility has emerged as the most feasible way to alleviate this problem. However, its potential depends heavily on the development of renewable energies. Island regions raise additional barriers to electromobility due to their heavy dependence on fossil fuels. This article addresses this challenge by presenting a comprehensive well-to-wheel framework to assess the levels of efficiency and CO2 emissions of electromobility options such as battery and plug-in electric vehicles (BEVs and PHEVs). The results were compared with those for internal combustion engine vehicles (ICEVs). The framework proposed takes account of various factors including the extraction, refining, and transport of oil, different segments of land vehicles, and electricity system operations. The framework is demonstrated with a case study of the Spanish Canary archipelago. The results show that BEVs improve efficiency and CO2 emissions by around 30% compared to ICEVs on islands where the share of renewable energies is higher than 21%. In contrast, limited renewable generation may lead to BEVs polluting up to 15% more than ICEVs. PHEVs should be considered as a suitable alternative if the share of renewable generation is higher than 35%. [ABSTRACT FROM AUTHOR]

Energy management in electrified vehicles is critical and directly impacts the global operating efficiency, durability, driveability, and safety of the vehicle powertrain. Given the multitude of components of these powertrains, the complexity of the proper control is significantly higher than the conventional internal combustion engine vehicle (ICEV). Hence, several control algorithms and numerical methods have been developed and implemented in order to optimize the operation of the hybrid powertrain while complying with the required boundary conditions. In this work, a model-based method is used for predicting the impacts of a set of possible control actions, choosing the one minimizing the associated costs. In particular, the energy management technique used in the present study is the equivalent consumption minimization strategy (ECMS). The novelty of this work consists of taking into account the thermal state of the ICE for optimization. This feature was implemented by means of an extensive experimental campaign at different coolant temperatures of the ICE to calibrate the additional fuel consumption due to operating the engine outside of its optimum temperature. The results showed significant gains in both WLTC and RDE cycles. [ABSTRACT FROM AUTHOR]

Hybrid electric vehicles are promising solutions to the need for cleaner transport. Their ability to drive fully electric also opens the possibility of zero local emission operation by turning off the internal combustion engine. However, prolonged periods with the engine turned off result in a cooldown of the aftertreatment system resulting in increased emissions when the engine is restarted. To remedy this problem, an emission management strategy that, based on pre-heating of the aftertreatment system, aims to reduce the impact of a prolonged engine-off event on NO x emissions is developed. The method works by locating each engine-off event and then handling each event separately using an optimization scheme that combines pre-heating and a causal heuristic emission management strategy. The individual events are linked using an equivalence factor that describes the decided trade-off between fuel and NO x . The equivalence factor can be chosen heuristically or iteratively to give the desired result in terms of NO x reduction and fuel consumption. The strategy is evaluated using simulations of a drayage drive cycle with multiple engine-off events. The results from the simulations show that for engine-off times below 0.5 h the strategy can reduce NO x compared to the baseline strategy while using the same amount of fuel. If the strategy is allowed more fuel, significant reductions in NO x can be seen for engine-off times up to 1.5 h, after which an exponential decay in the effectivity of the strategy is observed. It is also shown that the reduction in NO x is fairly linear in the equivalence factor, which gives the procedure of choosing it a predictable behavior. [ABSTRACT FROM AUTHOR]

The authors compare the energy consumption and CO2 emissions from vehicles using internal combustion engines (ICE), battery electric vehicles (BEV), fuel cell electric vehicles (FCEV), and two types of hybrid vehicles, BEV-ICE hybrid and BEV-FCEV hybrid. This paper considers several scenarios for four countries' electricity production from primary energy sources to estimate total CO2 release. Energy consumption of the vehicle per 100 km, emissions during manufacturing, battery production, and lifecycle of the vehicle are considered in the total amount evaluation of CO2 released. The results show that with current technologies for battery manufacturing, and a significant proportion of national grid electricity delivered by fossil fuels, BEV is the best choice to reduce carbon emissions for shorter driving ranges. In the case of electricity generation mainly by low-carbon sources, FCEV and BEV-FCEV hybrid vehicles end up with lower carbon dioxide emissions. In contrast, with electricity mainly generated from fossil fuels, electric vehicles do not reduce CO2 emissions compared to combustion cars. [ABSTRACT FROM AUTHOR]

The combination of electric motors and internal combustion engines in hybrid electric vehicles (HEV) can considerably improve the fuel efficiency compared to conventional vehicles. In order to use its full potential, a predictive intelligent control system using information about impending driving situations has to be developed, to determine the optimal gear shifting strategy and the torque split between the combustion engine and the electric motor. To further increase fuel efficiency, the vehicle velocity can be used as an additional degree of freedom and the development of a predictive algorithm calculating good choices for all degrees of freedom over time is necessary. In this paper, an optimization-based algorithm for combined energy management and economic driving over a limited horizon is proposed. The results are compared with results from an offline calculation, which determine the overall fuel savings potential through the use of a discrete dynamic programming algorithm. [ABSTRACT FROM AUTHOR]

Rapid vehicle and powertrain development has become essential to for the design and implementation of vehicles that meet and exceed the fuel efficiency, cost, and performance targets expected by today’s consumer while keeping pace with reduced development cycle and more frequent product releases. Recently, advances in large-scale additive manufacturing have provided the means to bridge hardware-in-the-loop (HIL) experimentation and preproduction mule chassis evaluation. This paper details the accelerated development of a printed range-extended electric vehicle (REEV) by Oak Ridge National Laboratory, by paralleling hardware-in-the-loop development of the powertrain with rapid chassis prototyping using big area additive manufacturing (BAAM). BAAM’s ability to accelerate the mule vehicle development from computer-aided design to vehicle build is explored. The use of a hardware-in-the-loop laboratory is described as it is applied to the design of a range-extended electric powertrain to be installed in a printed prototype vehicle. The integration of the powertrain and the opportunities and challenges it presents are described in this work. A comparison of offline simulation, HIL and chassis rolls results is presented to validate the development process. Chassis dynamometer results for battery electric and range extender operation are analyzed to show the benefits of the architecture. [ABSTRACT FROM AUTHOR]

Hybridization of heavy off-highway working vehicles brings considerable energy savings in the form of a downsized internal combustion engine (ICE) by means of reduced no-load losses. In this paper, a novel energy saving opportunity in working hydraulics at the end of long booms of working vehicles is proposed. In traditional off-highway working vehicles, the working hydraulics is supplied through pipes, hoses, and valves by a hydraulic pump located near the main engine. A significant amount of energy is lost in long pipelines and hoses as well as in valve throttles. A new topology is introduced to supply the power along the long boom; the power for a hydraulic actuator is supplied by an integrated electro-hydraulic energy converter (IEHEC), which is located at the boom end. The electrical energy to the converter is supplied through electrical cables, which have negligible losses compared with a conventional fluid power supply with long pipelines. The converter transforms the electrical energy into hydraulic energy at the end of the boom, and may also recover energy for additional energy savings. [ABSTRACT FROM AUTHOR]

This paper introduces a new low-cost hybrid drivetrain concept based on compressed air energy storage. In contrast to most contemporary approaches to pneumatic hybridization, which require modification to the primary power plant, this concept is based on a stand-alone pneumatic system that could be readily integrated with existing vehicles. The pneumatic system consists of an air tank and a compressor–expander that is coupled to the rest of the drivetrain via an infinitely variable transmission. Rather than incorporating more expensive technologies such as variable valve timing or a variable compression ratio compressor, a fixed valve system consisting of a rotary valve and passive check valves is optimized to operate efficiently over a range of tank pressures. The feasibility of this approach is established by thermodynamic modeling and the construction of a proof-of-concept prototype, which is also used to fine tune model parameters. While the proof-of-concept system shows a round trip efficiency of just under 10%, modeling shows that a round trip efficiency of 26% is possible with a revised design. If waste heat from the engine is used to maintain an elevated tank temperature, efficiencies of nearly 50% may be possible, indicating that the concept could be effective for practical hybridization of passenger vehicles. [ABSTRACT FROM AUTHOR]

Abstract: Vehicles powered with internal combustion engines (ICEs) are one of the main pollutant sources in large cities. Most of large cities (e.g. Amman, capital of Jordan) suffer from frequent traffic jams. This leads to frequent stops and starts, and hence, an increase in tailpipe emissions. One way to minimize emissions is to use electric motors in the powertrain configuration. In this study, the performance of a hybrid fuel cell (FC)/battery vehicle is investigated utilizing different worldwide driving cycles. Initially, a model of a mid-sized ICE vehicle is developed and validated against experimental tests. The ICE vehicle validated model is then modified to be driven with only an electric motor powered by a hybrid FC/battery system. The effect of driving pattern, which varies from city to city and from region to region, is investigated. A driving cycle that represents the driving patterns in Amman city is developed based on experimental data and then used to evaluate the performance of both ICE and hybrid FC/battery vehicle configurations. It is found that the performance of the hybrid FC/battery configuration is much better than the ICE version in terms of emissions, fuel economy, efficiency, and speed tracking error. [Copyright &y& Elsevier]

This paper presents a comparative study of induction machines (IMs) and interior permanent-magnet synchronous machines (IPMSMs) in traction applications. Machines are chosen to have similar ratings to operate in the same vector-controlled drive system and to achieve a fair comparison. Due to the dynamic nature of traction applications, static efficiency maps are not used. Instead, energy consumption is evaluated for both IMs and IPMSMs during typical drive cycles. Machine efficiency is also evaluated during the drive cycle to account for steady-state and transient conditions. The results of these comparisons show that the IPMSM can have higher efficiencies for most conditions. After comparing IMs and IPMSMs, loss minimization is integrated into the IM drive. Optimal flux commands are dynamically set, and then, energy and efficiency are compared with those of the IPMSM. Results show that IMs can achieve efficiencies comparable to the IPMSMs when loss minimization is applied. The efficiency gap between the IM and IPMSM is thus reduced, and these results are verified in both a hybrid electric vehicle simulator and a hardware-in-the-loop experimental setup. [ABSTRACT FROM AUTHOR]

Energy consumption and the associated environmental impact are a pressing challenge faced by the transportation sector. Emerging electric-drive vehicles have shown promises for substantial reductions in petroleum use and vehicle emissions. Their success, however, has been hindered by the limitations of energy storage technologies. Existing in-vehicle lithium-ion battery systems are bulky, expensive, and unreliable. Energy storage system (ESS) design and optimization is essential for emerging transportation electrification. This paper presents an integrated ESS modeling, design, and optimization framework targeting emerging electric-drive vehicles. A large-scale ESS modeling solution is first presented, which considers major runtime and long-term battery effects, and uses fast frequency-domain analysis techniques for efficient and accurate characterization of large-scale ESS. The proposed design framework unifies design-time optimization and runtime control. This conducts statistical optimization for ESS cost and lifetime, which jointly considers the variances of ESS due to manufacture tolerance and heterogeneous driver-specific runtime usage. This optimizes ESS design by incorporating complementary energy storage technologies, e.g., lithium-ion batteries and ultracapacitors. Using physical measurements of battery manufacture variation and real-world user driving profiles, our experimental study has demonstrated that the proposed framework effectively explores the statistical design space and produces cost-efficient ESS solutions with statistical system lifetime guarantees. [ABSTRACT FROM AUTHOR]

Abstract: The paper focuses on investigating thermal-transients effects, associated to intermittent use of internal combustion engine (ICE), on fuel economy and hydrocarbon (HC) emissions of series hybrid solar vehicles (HSVs). An offline, non-linear constrained optimization is set-up to individuate the ICE power trajectory that simultaneously minimizes fuel consumption, suitably operates the battery and fully exploits daily solar contribution. The results highlight the importance of including thermal transients in HSV energy management. The combined effects of engine, generator and battery losses, along with cranking energy and thermal transients, produce non-trivial solutions for the engine/generator group, which should not necessarily operate at its maximum efficiency. [Copyright &y& Elsevier]

As hybrid electric vehicles (HEVs) are gaining more popularity in the market, the rule of the energy management system in the hybrid drivetrain is escalating. This paper classifies and extensively overviews the state-of-the-art control strategies for HEVs. The pros and cons of each approach are discussed. From different perspectives, real-time solutions are qualitatively compared. Finally, a couple of important issues that should be addressed in future development of control strategies are suggested. The benefits of this paper are the following: 1) laying down a foundation for future improvements, 2) establishing a basis for comparing available methods, and 3) helping devoted researchers choose the right track, while avoiding doing that which has already been done. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes a modelling and dynamic control design process applicable to the development of fuel cell electric vehicles (FCEVs) and hybrid electric vehicles (HEVs). After an introduction to advanced propulsion technologies the development of FCEV at DaimlerChrysler is described, followed by a discussion on hydrogen as a fuel for FCEV and the challenges related to hydrogen storage. It is essential for advanced vehicles to obtain a range comparable to that of mass production vehicles sold today. Thus, there is a strong need to operate such vehicles with high efficiency and maximize the energy stored onboard a vehicle. A stochastic dynamic programming algorithm was developed and applied to the energy management of this FCEV, which allow fuel economy optimisation while keeping a good driveability. [Copyright &y& Elsevier]

Comprehensive evaluation of greenhouse gas emission reductions from alternative vehicle powertrains requires the use of a life cycle assessment methodology, which considers manufacturing, utilization and end-of-life phases of the vehicle and fuel production. However, vehicle powertrain technologies and regional electricity and fuel production characteristics are evolving rapidly, making such studies performed using current data obsolete in few years. For example, regional electricity generation mixes across the Canadian provinces are largely different, and they are likely to evolve with the introduction of renewable electricity. Hence, there is a general need for adaptable and flexible life cycle assessment frameworks for the transportation sector for rapid evaluation of GHG reductions using up-to-date data. The objective of this study is to develop an adaptive life cycle assessment framework for light duty vehicles that can incorporate critical new developments in vehicle powertrain technologies and changes in electricity and fuel supply. Conventional, hybrid, plug-in hybrid, battery electric and fuel cell powertrain types are included in the framework as parametrized models. Critical parameters related to vehicle size and battery capacity, fuel consumption, mileage, battery chemistry, vehicle hybridization, and electricity and fuel emission intensity are incorporated. The framework was demonstrated by applying it in the Canadian context with the analysis of scenarios associated with electricity grid emission intensity, mileage, battery capacity and battery chemistry. [ABSTRACT FROM AUTHOR]

Fuel consumption and emissions in parallel hybrid electric vehicles (HEVs) are directly linked to the way the load request to the wheels is managed between the internal combustion engine and the electric motor powered by the battery. A significant reduction in both consumption and emissions can be achieved by optimally controlling the power split on an entire driving mission (full horizon—FH). However, the entire driving path is often not predictable in real applications, hindering the fulfillment of the advantages gained through such an approach. An improvement can be achieved by exploiting more information available onboard, such as those derived from Advanced Driver Assistance Systems (ADAS) and vehicle connectivity (V2X). With this aim, the present work presents the design and verification, in a simulated environment, of an optimized controller for HEVs energy management, based on dynamic programming (DP) and receding horizon (RH) approaches. The control algorithm entails the partial knowledge of the driving mission, and its performance is assessed by evaluating fuel consumption related to a Worldwide harmonized Light vehicles Test Cycle (WLTC) under different control features (i.e., horizon length and update distance). The obtained results show a fuel consumption reduction comparable to that of the FH, with maximum drift from optimal consumption of less than 10%. [ABSTRACT FROM AUTHOR]

• COM-based models can control CA50 for different RCCI engine transient conditions. • Single-fuel RCCI operation with biofuels is a promising way to commercialize RCCI combustion. • Combustion mode-switching with COM-based models is required to capture transient RCCI emissions. • PHEVs with RCCI engine has the potential to reduce local and global emissions. Reactivity-controlled compression ignition (RCCI) is a promising energy conversion strategy to increase fuel efficiency and reduce nitrogen oxide (NOx) and soot emissions through improved in-cylinder combustion process. Considering the significant amount of conducted research and development on RCCI concept, the majority of the work has been performed under steady-state conditions. However, most thermal propulsion systems in transportation applications require operation under transient conditions. In the RCCI concept, it is crucial to investigate transient behavior over entire load conditions in order to minimize the engine-out emissions and meet new real driving emissions (RDE) legislation. This would help further close the gap between steady-state and transient operation in order to implement the RCCI concept into mass production. This work provides a comprehensive review of the performance and emissions analyses of the RCCI engines with the consideration of transient effects and vehicular applications. For this purpose, various simulation and experimental studies have been reviewed implementing different control strategies like control-oriented models particularly in dual-mode operating conditions. In addition, the application of the RCCI strategy in hybrid electric vehicle platforms using renewable fuels is also discussed. The discussion of the present review paper provides important insights for future research on the RCCI concept as a commercially viable energy conversion strategy for automotive applications. [ABSTRACT FROM AUTHOR]