Mild Hybrid Electric Vehicle Research Articles

Fuel consumption and emission improvements obtained using a mild hybrid electrical system on a vehicle equipped with a manual gearbox

The latest emission requirements for vehicles requires major improvement in vehicles fuel consumption and emission performance. For entry level range of vehicles, in order to keep the production costs low, the simplest choice of hybridization is the mild-hybrid system with integrated starter-generator (ISG). This paper contains a model of a mild-hybrid electric vehicle equipped with a manual gearbox and a model of conventional vehicle with focus on the emission performance. The goal of this paper is to find out the fuel consumption and emission of a mild hybrid electric vehicle by simulation and to show the improvements compared to a similar vehicle equipped with a conventional powertrain.

Drivability improvements obtained using a mild hybrid electrical system on a vehicle equipped with a manual gearbox

In order to fulfil the latest and future emission standards, all vehicles will need to be equipped with hybrid powertrains or advanced depollution systems. For low cost and entry level range of vehicles, in order to keep the production costs low, the simplest choice of hybridization is the mild-hybrid system with integrated starter-generator (ISG). This paper contains a model of a mild-hybrid electric vehicle equipped with a manual gearbox with focus on the drivability performance of the powertrain. The goal of this paper is to find out the drivability performances of a hybrid vehicle by simulation and to show the improvements compared to a similar vehicle equipped with a conventional powertrain.

GPS data integration to reduce driving emissions of MHEVs in real operating conditions

Increasingly emission reduction requests and environmental pollution cut require improved optimization of current transportations. Control strategies and latest vehicles technologies developed in the automotive industry must be optimized, taking into account more information is possible from cars sensors to save energy and reduce emissions. The paper presents a possible strategy for reducing emissions with integration of GPS data in a Mild Hybrid Electric Vehicle simulator. In this study, real GPS data are evaluated to improve the system and introduce real environmental conditions in the system. The data obtained are analysed selectively in the paper. This paper is aimed to investigate the impact of real conditions on fuel consumption. Through theoretical analysis, the conclusion will be drawn that GPS technology is attractive to reduction of emissions.

Distributed Energy and Thermal Management of a 48-V Diesel Mild Hybrid Electric Vehicle With Electrically Heated Catalyst

The 48-V diesel mild-hybrid electric vehicle equipped with an electrically heated catalyst is a cost-effective solution to reduce tailpipe emissions, while its supervisory control design is more challenging, due to cross-coupled energy and thermal subsystems. This article presents a distributed control design for the energy and thermal management system, aiming to optimize fuel economy and reduce catalyst warm-up time, by cooperation between electrical heating and engine load upshift. A control-oriented model of HEV and catalyst is developed, which captures the dynamics of the battery state of charge and catalyst temperature. The energy and thermal management problem is cast as a hybrid optimal control problem, to minimize entire trip fuel consumption under different switching (warm-up) times. An off-line solution method is designed to exploit the tradeoff between fuel and warm-up time based upon hybrid minimum principle and a nested shooting algorithm. For online implementation, a distributed supervisory control is proposed, which covers both cold-start and normal operations, and is compatible with the equivalent consumption minimization strategy. Both off-line and online methods are validated in simulation, using two driving cycles and five warm-up speeds.

A Method for the Combined Estimation of Battery State of Charge and State of Health Based on Artificial Neural Networks

This paper proposes a method for the combined estimation of the state of charge (SOC) and state of health (SOH) of batteries in hybrid and full electric vehicles. The technique is based on a set of five artificial neural networks that are used to tackle a regression and a classification task. In the method, the estimation of the SOC relies on the identification of the ageing of the battery and the estimation of the SOH depends on the behavior of the SOC in a recursive closed-loop. The networks are designed by means of training datasets collected during the experimental characterizations conducted in a laboratory environment. The lithium battery pack adopted during the study is designed to supply and store energy in a mild hybrid electric vehicle. The validation of the estimation method is performed by using real driving profiles acquired on-board of a vehicle. The obtained accuracy of the combined SOC and SOH estimator is around 97%, in line with the industrial requirements in the automotive sector. The promising results in terms of accuracy encourage to deepen the experimental validation with a deployment on a vehicle battery management system.

Potential of hybrid powertrains in a variable compression ratio downsized turbocharged VVA Spark Ignition engine

After the diesel emissions scandal, also known as Dieselgate, Direct Injection Spark-Ignited (DISI) internal combustion engines (ICE) appears as the most promising alternative to mitigate the harmful tailpipe emissions from passenger cars. In spite of that, the current ICE technologies are not enough to achieve the fuel consumption/CO2 emissions targets set by the new transportation legislation (4.1 Lgasoline/100 km, 95 gCO2/km for 2021). In this complex scenario, the electrification of the powertrain using high efficiency electric motors and battery package together with sophisticated DISI engines appears as potential solution to meet these requirements. The aim of this work is to study the fuel consumption and pollutant emissions in transient conditions from a passenger car equipped with a variable compression ratio (VCR) DISI engine and electrified powertrain technologies. The vehicle behavior was simulated by means of a 0D GT-Suite model fed by experimental results obtained in an engine test bench. Mild hybrid electric vehicle (MHEV) and full hybrid electric vehicle (FHEV) architectures using a VCR DISI engine were studied. Moreover, an optimization methodology is presented to select the best vehicle configuration in terms of hardware and control strategies by means of a design of experiments (DoE). The results show that VCR allows a fuel improvement of 3% with respect to the conventional DISI fixed CR along the worldwide harmonized light vehicles test cycles (WLTC). The benefits found when combining the VCR technology with hybrid powertrains are even higher. In this sense, the fuel improvements were higher as the electrification levels increased, with 8% for MHEV-VCR and around 20% for FHEV-VCR. In terms of emissions, the two clear benefits with FHEV-VCR were the reduction of particle number (PN) and unburned hydrocarbons (HC) of around 60% and 15%, respectively, as compared to the conventional DISI.

Comparative Concept Study of Passive Hybrid Energy Storage Systems in 48 V Mild Hybrid Vehicles Varying Lithium-Ion Battery and Supercapacitor Technologies

A single energy storage technology will deliver either high power or high energy density. In high cycle applications like 48 V mild hybrid electric vehicles, lithium-ion batteries or supercapacitors have to be oversized to meet power, energy and cycle life requirements. However, a passive hybrid energy storage system is able to meet those challenges, but its performance depends on several factors. In this study, simulations and experimental investigations show how the design and operation conditions influence the performance of a passive hybridized system. In a comparative study for 48 V systems, consequences on performance are discussed.

Electric Motor and Dry Clutch Control in Launch Manoeuvres of Mild-Hybrid Vehicles Based on AMT/DCT Transmissions

Mild-Hybrid Electric Vehicles (mild-HEVs) earned market share over the last years an as effective roadmap to limit air pollution in big cities. In addition to this role, hybrid propulsion can be used to avoid dry clutch overheating in mild-HEVs equipped with automated manual transmissions. Indeed, high thermal level could result in serious damaging of dry clutch linings with very fast decay of expected lifespan affecting vehicle reliability. This paper shows results of vehicle launch simulations to highlight how the propulsion due to electric motor can effectively reduce clutch thermal stress during the slipping phase.

Emissions reduction from passenger cars with RCCI plug-in hybrid electric vehicle technology

Hybrid Electric Vehicles (HEVs) can be considered as a potential technology to promote the change from conventional mobility to e-mobility. However, the real benefits in terms of CO2 emissions depend on a great extent on their mode of use, vehicle design and electricity source. On the other hand, in the last few years, advanced combustion modes as Reactivity Controlled Compression Ignition (RCCI) showed great advantages in terms of NOx and soot emissions reduction. This paper has the purpose of assessing, through numerical simulations fed with experimental results, the potential of different hybrid vehicles when used together with a low temperature combustion mode. In particular, the dual-fuel Mild (MHEV), Full (FHEV) and Plug-in (PHEV) hybrid electric vehicles are tested and compared to the original equipment manufacturer (OEM) and the conventional dual-fuel powertrain, both no-Hybrid vehicles. The powertrains are optimized to meet the current European homologation legislation Worldwide Harmonized Light Vehicle Test Procedure (WLTP). After that, a deep analysis is performed in terms of performance and emissions. Lastly, a life-cycle analysis (LCA) is performed to evaluate the real potential of the different technologies. The results show that the PHEV has the highest benefits in terms of fuel consumption and engine-out emissions. With this technology, it is possible to achieve the 50 g/km CO2 target for the PHEVs with a medium battery size (15 kWh), while NOx and soot levels are under the Euro 6 limits. In addition, the RCCI technology shows great benefits to achieve the Euro6 soot level for the other hybrid platforms. The LCA shows that the PHEVs can achieve 12% reduction of the total CO2 with respect to the FHEVs, and 30% with respect to the no-hybrid diesel platform.

Quad‐bus motor drive system for electrified vehicles based on a dual‐output–single‐inductor structure

48 V electric system architecture has been recently introduced to accommodate an increasing number of electric components in mild hybrid electric vehicles. In this study, two additional DC buses are added for electric machines including 36 and 24 V AC- and DC-motor/actuator loads, in a 48/12 V power supply system. This structure can yield significant benefits, especially for electrified vehicles that have more electric machines and actuators. A single-inductor multi-output structure is employed, with a control strategy that produces linear transfer functions and is less sensitive to load variation, to accommodate multiple-bus motor/actuator drives. The proposed structure and control strategy can offer options for selecting proper bus voltages, optimising the electric machine's power density. Both simulations and experiments have been performed to verify the system structure and control schemes using 36 and 24 V electric machines connected to the additional dual-output buses on top of the existing 12/48 V bus structure.

A review on opportunities of thermionic regeneration system in hybrid electric vehicle

A hybrid electric vehicle utilizes power from both engine and battery to drive the wheels. Hybrid electric vehicle architectures are micro, mild, full and plug in hybrids. This review covers recent optimization in technologies and systems of hybrid electric vehicle. It is evident from the literature that utilizing waste energy such as braking losses for battery charging is more effective for micro and mild hybrid electric vehicle. The increase in electrification increases the demand of alternate battery charging methods in vehicle. Therefore, the opportunity lies in recovering waste heat of engine for battery charging. This could be done by direct energy converters such as thermoelectric and thermionic converters. The paper comprehensively studies these direct energy converters on the basis of their working principle and conversion efficiencies. The results from this study show that thermionic energy conversion stands better for hybrid electric vehicles as compared with other direct energy conversion methods.

Estimation Accuracy and Computational Cost Analysis of Artificial Neural Networks for State of Charge Estimation in Lithium Batteries

This paper presents a tradeoff analysis in terms of accuracy and computational cost between different architectures of artificial neural networks for the State of Charge (SOC) estimation of lithium batteries in hybrid and electric vehicles. The considered layouts are partly selected from the literature on SOC estimation, and partly are novel proposals that have been demonstrated to be effective in executing estimation tasks in other engineering fields. One of the architectures, the Nonlinear Autoregressive Neural Network with Exogenous Input (NARX), is presented with an unconventional layout that exploits a preliminary routine, which allows setting of the feedback initial value to avoid estimation divergence. The presented solutions are compared in terms of estimation accuracy, duration of the training process, robustness to the noise in the current measurement, and to the inaccuracy on the initial estimation. Moreover, the algorithms are implemented on an electronic control unit in serial communication with a computer, which emulates a real vehicle, so as to compare their computational costs. The proposed unconventional NARX architecture outperforms the other solutions. The battery pack that is used to design and test the networks is a 20 kW pack for a mild hybrid electric vehicle, whilst the adopted training, validation and test datasets are obtained from the driving cycles of a real car and from standard profiles.

TC48: A low‐cost 48 V integrated drive for mild hybrid electric vehicles

The TC48 drive is a low-cost, low-voltage integrated motor-drive solution suitable for mild hybrid electric vehicles, off-highway traction, and any application where a compact, highly torque-dense machine is required. Low-voltage solutions for electric vehicles are attractive to manufacturers due to lower insulation requirements, and hence lower cost. The package is based on a six-phase switched reluctance machine, which uses a novel stator topology and unique winding design to achieve high torque density. The power electronics converter hardware is integrated into the motor housing, giving a physically, electrically, and thermally optimised solution. The complete package has been designed to be suitable for manufacturing in high volumes. This study describes the electromagnetic design of the motor, the mechanical innovations used to physically realise this design, and the cooling system which makes the high power density possible. The integration of the power electronics and their control is also discussed. The project is the result of collaboration between Newcastle and Loughbosrough Universities, RDM Ltd., Productiv, Infineon, Tata Steel, and Libralato.

Power Management Strategy for the 48 V Mild Hybrid Electric Vehicle Based on the Charge-Sustaining Control

To enhance the 48 V mild hybrid electric vehicle performance using a smaller capacity and lower voltage battery than the full hybrid electric vehicle, a novel power management strategy needs to be established that considers the characteristics and limitations of the components. This paper proposes a charge-sustaining control strategy as a ground principle of the 48 V hybrid electric vehicle control for managing the battery state-of-charge (SOC) to stay near the most efficient regime. The base efficiency characteristics of the component models including engine, motor/generator, and battery are determined in the form of efficiency maps using the powertrain analysis tool. Then the control strategy is formulated as a nonlinear optimal regulation problem that meets two conflicting control objectives, such as fuel efficiency improvement and state-of-charge maintenance. The optimal regulation problem implements a discrete-time Hamilton-Jacobi-Bellman approach. The proposed strategy is evaluated by comparing with the reference strategy applying the Dynamic Programming (DP), i.e. a global optimal result, under urban dynamometer driving schedule and worldwide harmonized light duty test cycle. Through the evaluation, the fuel efficiency of the proposed strategy with three different electrical loads is slightly deteriorated at most by 5.03 % from the DP results with staying within a desirable SOC. This suggests that the proposed strategy is operating very closely to global optimal performances.

Aging characterization and modeling of nickel-manganese-cobalt lithium-ion batteries for 48V mild hybrid electric vehicle applications

Abstract This paper investigates the cycle aging behavior of nickel-manganese-cobalt (NMC) lithium ion battery cells under high current rates and narrow window of State-of-Charge (SOC) variation for 48 V mild hybrid electric vehicle (HEV) applications. The charge sustaining aging profiles were synthesized from real-world duty cycles in some of the authors’ previous work [44,45] and used in the laboratory for life cycle aging testing spaced out by periodic cell capacity tests performed to assess cell aging conditions. Furthermore, at each 1C discharged aging characterization stage, the parameters of a physics-based electrochemical cell model were identified using the Bayesian Markov Chain Monte Carlo (MCMC) method. Among the parameters that can be identified with sufficient accuracy from the experimental data, the concentration of lithium-ions at the negative electrode after full charge is found to be strongly correlated with the system-level loss of capacity. These results provide new insights on the aging performance of NMC lithium ion cells in battery management system for 48 V hybrid vehicles.

Cost-efficient Thermal Management for a 48V Li-ion Battery in a Mild Hybrid Electric Vehicle

The 48V mild hybrid system is a cost-efficient solution for original equipment manufacturers to meet increasingly stringent fuel consumption requirements. However, hybrid functions such as auto-stop/start and brake regeneration are unavailable when a 48V battery is at very low temperature because of its limited charge and discharge capability. Therefore, it is important to develop cost-efficient thermal management to warm-up the battery of a 48V mild hybrid electric vehicle (HEV) to recover hybrid functions quickly in cold climate. Following the model-based “V” process, we first define the requirements and then design different mechanisms to heat a 48V battery. Afterward, we build a 48V battery model in LMS AMESim and conduct co-simulation with simplified battery management system and hybrid control unit algorithms in MATLAB Simulink for analysis. Finally, we carry out a series of vehicle experiments at low temperature and observe the effect of heating to validate the design. Both simulation results and experimental data show that a cold 48V battery placed in a cabin with hot air can be heated effectively in the developed “Enhanced Generator Mode with 48V Battery” mode. The entire design is in a newly developed software that cyclically charges and discharges a 48V battery for quick warm-up in cold temperature without needing any additional hardware such as a heater, making it a cost-efficient solution for HEVs.

Efficient 48V Application

Research and development into 48V applications in mild hybrid electric vehicles calls for efficient delivery of power, overcoming the challenges of belt-driven systems

Comparative fuel economy, cost and emissions analysis of a novel mild hybrid and conventional vehicles

Mild hybrid vehicles have been explored as a potential pathway to reduce vehicle emissions cost-effectively. The use of manual transmissions to develop novel hybrid vehicles provides an alternate route to producing low cost electrified powertrains. In this paper, a comparative analysis examining a conventional vehicle and a mild hybrid electric vehicle is presented. The analysis considers fuel economy, capital and ongoing costs and environmental emissions, and includes developmental analysis and simulation using mathematical models. Vehicle emissions (nitrogen oxides, carbon monoxide and hydrocarbons) and fuel economy are computed, analysed and compared using a number of alternative driving cycles and their weighted combination. Different driver styles are also evaluated. Studying the relationship between the fuel economy and driveability, where driveability is addressed using fuel-economical gear shift strategies. Our simulation suggests the hybrid concept presented can deliver fuel economy gains of between 5 and 10%, as compared to the conventional powertrain.

Effects of using Synthesized Driving Cycles on Vehicle Fuel Consumption

Creating a driving cycle (DC) for the design and validation of new vehicles is an important step that will influence the efficiency, functionality and performance of the final systems. In this work, a DC synthesis method is introduced, based on multi-dimensional Markov Chain, where both the velocity and road slope are investigated. Particularly, improvements on the DC synthesis method are proposed, to reach a more realistic slope profile and more accurate fuel consumption and CO2 emission estimates. The effects of using synthesized DCs on fuel consumption are investigated considering three different vehicle models: conventional ICE, and full hybrid and mild hybrid electric vehicles. Results show that short but representative synthetic DCs will results in more realistic fuel consumption estimates (e.g. in the 5%-10% range) and in much faster simulations. Using the results of this proposed method also eliminates the need to use very simplified DCs, as the New European Driving Cycle(NEDC), or long, measured DCs.

병렬제어기법이 적용된 1.8kW급 마일드 하이브리드 양방향 LDC 설계 및 구현

병렬제어기법이 적용된 1.8kW급 마일드 하이브리드 양방향 LDC 설계 및 구현