Series Hybrid Research Articles

Assessment of air management strategies to improve the transient response of advanced gasoline engines operating under high EGR conditions

Advanced gasoline engines may lead the medium-term future of the passenger vehicle market, working in conventional and hybrid powertrains. Downsizing with turbocharging is the most extended way to improve fuel economy in gasoline engines. It is also proven that exhaust gas recirculation (EGR) reduces fuel consumption, but extracting the maximum benefit from EGR requires operating with high EGR rates. This fact can compromise the transient engine operation due to the greater turbocharger dependence. This research evaluates the EGR influence on the transient response of a turbocharged gasoline engine and, mainly, the potential of three air management strategies to accelerate the said response. Tip-in maneuvers at 1500 rpm (6–12 bar BMEP) were tested and simulated to this end. The three strategies are: reducing the EGR dilution by closing the EGR valve simultaneously with the throttle opening, using a pressurized air tank (PAT), and installing an electric supercharger at the compressor outlet in series. Engine tests show that the torque response time with EGR is 2-s slower than without EGR. 1D modeling results reveal that: the PAT connected to the intake manifold provides the fastest response, and the electric supercharger guarantees an excellent tradeoff between fuel consumption and torque response.

Performance Measures for Evaluating the Accuracy of Time Series Hybrid Model Using High Frequency Data

Given that the traditional ARIMAX model has rarely been applied to any of the climate change and environmental agents, which are the most cognate agents with associated exogenous variables; to neutralize the model for a better and enhanced prediction of the system, a distributional form of the error term that is robust and sufficient in capturing and accommodating both the external covariate(s) and high frequency data is required. This study therefore evaluates the forecasting accuracy of two forecasting models namely ARIMAX and log-ARIMAX. The monthly adjusted high frequency data recorded by four Oil and Gas companies from 2005 – 2020 were used. The forecastability of the two models was evaluated with different error matrices. The effect of Akaike Information Criterion (AIC) and the linear correlation on candidate models among the considered oil spill data tested were discussed. Results for ARIMAX and LOG-ARIMAX Models selection with respect to AIC show that log-ARIMAX is more efficient and performed better than the traditional ARIMAX model for observations characterized by kurtosis, skewness, outliers, high frequency and large fluctuation series with heavy tailed traits as seen in environmental data.

Fuzzy Logic-Based Energy Management Strategy of Hybrid Electric Propulsion System for Fixed-Wing VTOL Aircraft

An energy management strategy for a series hybrid electric propulsion system designed for a fixed-wing vertical take-off and landing (VTOL) aircraft is presented in this paper. The proposed method combines an ideal operating line (IOL) and fuzzy logic. Fuzzy logic is used to dynamically and optimally allocate the output power of the generator and the battery pack according to the power requirement of the aircraft and the SOC of the battery pack. The IOL controller is used to optimize the internal combustion engine (ICE) operating point to improve the fuel economy of the system. The detailed aircraft model and energy system model are established. The flight process of a 100 kg scale VTOL aircraft under a typical mission profile is simulated. The simulation results show that running the ICE based on IOL can greatly improve its efficiency The introduction of fuzzy logic to optimize the power allocation of the generator and battery pack improves the overall efficiency of the system. The feasibility and effectiveness of the energy management strategy proposed in this paper are verified, and the design ideas and analysis methods are provided for the energy management of a hybrid electric aircraft.

Optimal Powertrain Sizing of Series Hybrid Coach Running on Diesel and HVO for Lifetime Carbon Footprint and Total Cost Minimisation

This article aims to calculate, analyse and compare the optimal powertrain sizing solutions for a long-haul plug-in series hybrid coach running on diesel and hydrotreated vegetable oil (HVO) using a co-design optimisation approach for: (1) lowering lifetime carbon footprint; (2) minimising the total cost of ownership (TCO); (3) finding the right sizing compromise between environmental impact and economic feasibility for the two fuel cases. The current vehicle use case derived from the EU H2020 LONGRUN project features electrical auxiliary loads and a 100 km zero urban emission range requiring a considerable battery size, which makes its low carbon footprint and cost-effective sizing a crucial challenge. Changing the objective between environmental impact and overall cost minimisation or switching the energy source from diesel to renewable HVO could also significantly affect the optimal powertrain dimensions. The approach uses particle swarm optimisation in the outer sizing loop while energy management is implemented using an adaptive equivalent consumption minimisation strategy (A-ECMS). Usage of HVO fuel over diesel offered an approximately 62% reduction in lifetime carbon footprint for around a 12.5% increase in overall costs across all sizing solutions. For such an unconventional powertrain topology, the fuel economy-focused solution neither achieved the lowest carbon footprint nor overall costs. In comparison, CO2−cost balanced sizing resulted in reductions close to the single objective-focused solutions (5.7% against 5.9% for the CO2 solution, 7.7% against 7.9% for the TCO solution on HVO) with lowered compromise on other side targets (CO2 reduction of 5.7% against 4.9% found in the TCO-focused solution, TCO lowering of 7.7% against 4.4% found in the CO2-focused solution).

Real Time Predictive and Adaptive Hybrid Powertrain Control Development via Neuroevolution

The real-time application of powertrain-based predictive energy management (PrEM) brings the prospect of additional energy savings for hybrid powertrains. Torque split optimal control methodologies have been a focus in the automotive industry and academia for many years. Their real-time application in modern vehicles is, however, still lagging behind. While conventional exact and non-exact optimal control techniques such as Dynamic Programming and Model Predictive Control have been demonstrated, they suffer from the curse of dimensionality and quickly display limitations with high system complexity and highly stochastic environment operation. This paper demonstrates that Neuroevolution associated drive cycle classification algorithms can infer optimal control strategies for any system complexity and environment, hence streamlining and speeding up the control development process. Neuroevolution also circumvents the integration of low fidelity online plant models, further avoiding prohibitive embedded computing requirements and fidelity loss. This brings the prospect of optimal control to complex multi-physics system applications. The methodology presented here covers the development of the drive cycles used to train and validate the neurocontrollers and classifiers, as well as the application of the Neuroevolution process.

Modelling and Performance Analysis of an Autonomous Marine Vehicle Powered by a Fuel Cell Hybrid Powertrain

This paper describes the implementation of a hydrogen-based system for an autonomous surface vehicle in an effort to reduce environmental impact and increase driving range. In a suitable computational environment, the dynamic electrical model of the entire hybrid powertrain, consisting of a proton exchange membrane fuel cell, a hydrogen metal hydride storage system, a lithium battery, two brushless DC motors, and two control subsystems, is implemented. The developed calculation tool is used to perform the dynamic analysis of the hybrid propulsion system during four different operating journeys, investigating the performance achieved to examine the obtained performance, determine the feasibility of the work runs and highlight the critical points. During the trips, the engine shows fluctuating performance trends while the energy consumption reaches 1087 Wh for the fuel cell (corresponding to 71 g of hydrogen) and 370 Wh for the battery, consuming almost all the energy stored on board.

Integrated Optimal Design for Hybrid Electric Powertrain of Future Aircrafts

This paper presents the integrated optimal design of the powertrain of a hybrid regional aircraft using multidisciplinary design optimization (MDO). The sizing of the main components of the propulsion chain is performed over the flight mission under various scenarios regarding energy management strategies and technological assessments. For that purpose, a complete set of multidisciplinary surrogate models are integrated into the MDO process, taking account not only of the main electrical, thermal and mechanical aspects but also of environmental constraints such as partial discharges in electric motors regarding flight conditions. Several MDO formulations are investigated comparing local (i.e., motor mass minimization) and global optimizations (i.e., powertrain mass then fuel burn minimization at aircraft level). Results emphasize main systemic couplings showing that despite future technological progress, the series hybrid architecture is heavier than a conventional thermal aircraft. Nevertheless, thanks to the whole aircraft optimization, potential gains related to kerosene consumption can be reached, reducing the environmental footprint. The “energy gains” focused on in this paper may be added with aerodynamic gains potentially involved in more electric powertrain. This work has been carried out in the frame of the HASTECS project under the Clean Sky II program which aims at reducing CO2 emissions and environmental impacts of the aviation sector.

JUSTIFICATION OF THE PARAMETERS OF THE PASSENGER CAR SERIES HYBRID POWER PLAN

The use of hybrid power plants in road transport can significantly improve driving dynamics and driving comfort, reduce its operating fuel consumption and emissions of harmful substances with exhaust gases. Due to the large number of used cars with internal combustion engines (ICE) in Ukraine, it is of interest to convert them into a hybrid power drive. However, the analysis of the literature revealed extremely limited information about the work in this direction. The paper proposes a method for selecting the parameters of elements of a series hybrid power drive based on a used Chevrolet Lacetti car. The technique is based on the use of mathematical models of the working process of the internal combustion engine, the dynamics of the acceleration of the car, the determination of the parameters of the series hybrid power plant in the modes of the European NEDC test cycle. Using the developed mathematical models, the rated power of the traction electric motor is 86 kW, the nominal and maximum rotational speed of its shaft, respectively, are 1860 and 7000 min-1. It is shown that the car will accelerate to 100 km/h in 11.4 seconds, which fully satisfies the conditions of comfortable driving in urban conditions. As part of a hybrid power plant, the internal combustion engine operates in one mode. The paper substantiates the choice of the operating mode of the internal combustion engine, where it has the best fuel efficiency. At the same time, its power is 34 kW, and the crankshaft speed is 2200 min-1. Accordingly, the power of the current generator will be 30 kW at a shaft speed of 2200 min-1. The paper analyzes the influence of the battery capacity, the presence of braking energy recuperation, the operating range of battery capacity change on the average operating fuel consumption of internal combustion engines. It is shown that an increase in the battery capacity, the presence of recuperation, and the expansion of the operating range of changes in the battery capacity lead to an improvement in the operational fuel efficiency of an internal combustion engine. Based on the results of computational studies, the maximum battery capacity of 1.3 kWh was selected; the operating range of capacity change was 0.8 kWh. The use of elements with such parameters will ensure the average operating fuel consumption of the internal combustion engine is 6.5 l/100 km, and with the recovery of braking energy - 6 l/100 km.

Comparative evaluation of classic and seasonal time series hybrid models in predicting electrical conductivity of Maroun river, Iran

Comparative evaluation of classic and seasonal time series hybrid models in predicting electrical conductivity of Maroun river, Iran

Optimal Eco-Routing for Hybrid Vehicles With Powertrain Model Embedded

Exploiting the full potential of hybrid electric vehicles (HEVs) requires suitable (i) route selection and (ii) power management. Due to coupling of the two subproblems, an integrated optimization problem is desired, i.e., optimizing simultaneously the route selection and the split between combustion engine and electric motor over the entire route selection. The resulting optimal route and vehicle operation can be used as a basis for a subordinate vehicle controller. We present an eco-routing approach that embeds a hybrid (mechanistic/data-driven) model of the HEV powertrain in an integrated routing and power management optimization problem. Formulating the integrated routing problem with the hybrid model yields a mixed-integer bilinear program which we reformulate and solve a mixed-integer linear program using a state-of-the-art solver. The results show the validity of the developed hybrid powertrain model and demonstrate that the eco routing approach with the powertrain model embedded can be applied to large-scale problems. We consider optimization for minimal travel time and minimum fuel consumption. The latter results in fuel demand reductions up to 70 %. Alternatively, we minimize the fuel consumption while constraining the travel time to a maximum value resulting in up to 50 % fuel demand reductions. The highest fuel demand reductions are achieved in urban environments. The entire framework is written in python and provided as an open-source version (MIT License) under <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://git.rwth-aachen.de/avt-svt/public/optimal-routing</uri> that can readily be applied.

Real-Time Multiobjective Energy Management for Electrified Powertrains: A Convex Optimization-Driven Predictive Approach

Energy management is an important technology for maximizing the energy efficiency of hybrid vehicles. In the process of developing cost-optimal powertrain control strategies, existing studies have explored the interactions between fuel economy and battery degradation to prolong the battery service period and reduce fuel consumption simultaneously. However, computational efficiency will be sacrificed in order to search optimal control sequences due to the nonlinear powertrain model and many optimization variables in the optimal control problem, which hinders the implementation in real-time applications. To this end, this article combines second-order cone programming and model predictive control algorithms to formulate a computationally efficient energy management strategy for a series hybrid electric vehicle. Specifically, three main contributions are made which distinguish our work from existing studies. First, based on the constructed convex powertrain model, two objectives, fuel economy and battery degradation, are optimized by the proposed hybrid algorithm. Second, a comparison study that compares the strategies with and without battery degradation optimization is presented to validate the effectiveness of the proposed control strategy. Finally, by changing the size of the prediction horizon, several simulation results are discussed to evaluate the computational efficiency of the devised method. Furthermore, the effects of different battery and fuel prices on optimized results are analyzed.

Regulated Series Hybrid Converter With DC Transformer (DCX) for Step-Up Power Conversion

The partial power converter, which is composed of isolated topology and dc–dc topology is getting more and more attention due to its efficient power delivery. This article proposes a partial power regulated series hybrid converter (RSHC), which is suitable for power conversion in step-up isolated applications. The proposed RSHC architecture consists of a dc–dc converter aiming to regulate the output voltage and a secondary-side series resonant converter (SSRC) operating as a high-efficiency dc transformer (DCX). The resonant tank of SSRC is derived from the reverse structure of a conventional LLC resonant converter. Different from the two-stage structure, the bulk power from the input to output is directly transmitted by SSRC with DCX function (SSRC-DCX), and part of the total power is delivered by dc–dc converter. Moreover, the voltage stress across the power devices of the dc–dc converter in the proposed RSHC is reduced in comparison with the two-stage structure. Therefore, the proposed RSHC can improve efficiency as well as save costs. The steady-state operation principle of RSHC is analyzed. Finally, a 250 W prototype is built to verify the output regulation mechanism and performance of the proposed RSHC.

Investigation of the Series Hybrid Electric Powertrain Architecture with Wankel Engine as a Range Extender

In this study, a conventional vehicle is converted into a series hybrid electric vehicle. Electric motor power, battery pack capacity, range extender operating condition is determined; a computational model of the vehicle is built and simulations are conducted using Worldwide Harmonized Light Vehicles Test Procedure (WLTP). Power rating of the electric motor is calculated as 120 kW for the same acceleration performance. Wankel engine data available in the Automotive Laboratory of Istanbul Technical University are used. Energy capacity of battery pack is determined according to the daily driving distance of the WLTP. Engine on-off control strategy is used to control range extender operation. Wankel engine is operated at a speed of 4000 rpm and load of 5.15 bar, hence it is tuned to deliver an output power of 22.3 kW. Simulation results show that the performance of Wankel engine is validated as range extender by using engine on-off control strategy. State of charge of battery pack is set as minimum (30%) at the beginning of simulation and the state of charge of the battery pack charged by the range extender is assumed to be approximately 50% at the end of the cycle. For comparison, performance of Wankel engine is compared to the range extender of a mass-produced series hybrid electric vehicle, which has a battery pack capacity of 18.8 kWh. In conclusion, it is shown that a more compact range extender unit with a battery pack of 35 kWh is advantageous from the perspective of the packaging of the battery pack.

Online Updating Energy Management Strategy Based on Deep Reinforcement Learning With Accelerated Training for Hybrid Electric Tracked Vehicles

An online updating energy management strategy (EMS) based on deep reinforcement learning (DRL) with accelerated training is proposed to further reduce fuel consumption and improve the adaptability of the algorithm. The online frame continuously updates neural network parameters every predetermined time. First, the mathematical model of a series hybrid electric tracked vehicle (SHETV) is established, and the accuracy of the model is verified by collecting data from the real vehicle. Second, an intelligent EMS is developed by combining deep deterministic policy gradient (DDPG) and prioritized experience replay (PER). DDPG can improve the control effect and accelerate the training process by eliminating the discretization of variables. The addition of PER can further improve fuel economy and SOC performance and shorten the training time. Third, an online updating framework based on DDPG-PER is proposed to make EMS better adapt to complex driving conditions. Finally, a software-in-the-loop simulation is built, and the effectiveness of the proposed online updating EMS is verified by comparison with other state-of-the-art algorithms. Simulation results show that the training process of the off-line EMS is greatly accelerated, which provides a potential for online application. Meanwhile, the fuel economy of the online updating EMS reached 93.9% of the benchmark DP.

Analysis of Energy Flow in the Hybrid Power-Split (PS) System of SUV Vehicle in Real Driving Conditions (RDC)

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Hybrid powertrains are replacing conventional combustion drives at an accelerating rate, while offering a reduction in fuel consumption and toxic exhaust emissions. The large share of hybrid solutions in engine vehicles has been observed for the compact class and in SUVs. The Authors of this study proposed an energy flow assessment in the hybrid powertrain system of an SUV in various driving conditions: urban, extra-urban and motorway. The tests were performed in accordance with the stipulations of the RDC test conditions and its requirements. The tests were carried out on a Toyota RAV4 HEV equipped with a 2.5 dm&lt;sup&gt;3&lt;/sup&gt; engine in a hybrid drive system along with Li-Ion batteries, which had an energy capacity of 1.11 kWh (4.3 Ah). The research was carried out on an urban route in Poznan as well as in its vicinity using three drive modes of the drive system: Eco, Normal and Sport. Based on the results of energy flow tests, it was found that, regardless of the initial state of charge (SOC) of battery, the vehicle would reach constant SOC values in the second phase of the test - in the extra-urban driving phase. Such conditions stabilize after about 30 km of urban driving. The differences in the range of these SOC values were around 10%. Due to the conditions of motorway driving, the SOC changes were very small and amounted to about 3-5% while covering about 20 km (in this driving mode). The tests confirmed the slight influence that the driving mode (eco, normal, sport) had on the final measured charge values: for discharge, charging or regeneration. The share of time operating in electric mode for individual test phases was also determined, and it was approximately 65-68%, 25-30% and 5-8% in the urban, extra-urban and motorway phases, respectively.&lt;/div&gt;&lt;/div&gt;

Testing of a Modern Wankel Rotary Engine - Part IV: Overall Mechanical and Thermal Balance

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;The present work extends the performance analysis of a rotary Wankel engine for range extender applications already introduced in the companion papers of this series. Specifically, in this work, an overall balance was carried out on mechanical and thermal parameters inferred from the indicated pressure cycles and those measured by the dynamometer and the data acquisition system during steady-state engine testing, highlighting the energy fluxes within the machine. The evaluation of the in-chamber heat transfer coefficient, by means of an adapted Woschni model, and the related heat rejected to the coolant represent the additional and necessary analysis to complete the experimental assessment already presented in the previous papers. The tested engine is the Advanced Innovative Engineering 225CS and the experimental testing was conducted using a combustion analyser specifically developed for rotary machines. The results reported in this work are representative of the performance of current rotary engine technology. The engine was tested in steady-state motored and firing conditions while collecting all the usual engine data. The indicated torque, the net heat release and the rate of heat release were computed from the indicated pressure cycle taking into account the engine geometrical parameters and employing analytical relations and numerical procedures. The indicated torque at different operating points was compared under further simplifying assumptions (friction torque curve measured in motoring condition considered unaltered in firing condition) with the motoring and firing torque measured by the dynamometer while the net heat released was compared with the instantaneous fuel flow rate, the mechanical power delivered and the heat rejected in the coolant. The results show a good balance closure of the aforementioned parameters with a low level of imbalance mainly due to simplifying assumptions and measurement uncertainties, hence validating the methodologies extensively reported in Part II and III of this suite of papers. The data reported here and in the previous works also represent the initial steps in validating CFD models and the optimisation of fuel consumption and emissions for the aforementioned engine to be employed as a range extender in Series Hybrid (or Range-Extended) Electric Vehicles.&lt;/div&gt;&lt;/div&gt;

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.

Modeling of a Hybrid Fuel Cell Powertrain with Power Split Logic for Onboard Energy Management Using a Longitudinal Dynamics Simulation Tool

This work aims to develop a mathematical model for the simulation of a fuel cell (FC) hybrid powertrain. The work starts from modeling a single cell to obtain information on the entire FC stack. The model obtained was integrated into a simulation tool presented in the literature that simulates the longitudinal dynamics of auxiliary power unit hybrid electric vehicles and fully electric vehicles. Therefore, the integrated model allows the simulation of hybrid vehicles equipped with FC and a battery pack that acts as a peak power source. The tool simulates the mechanical and electrical behavior of the vehicle, introducing an investigation of the power flows relating to the FC and batteries. An appropriate power split logic has been implemented, allowing the correct management of the power distribution between the FC and the batteries. The importance of analyzing FC vehicles’ behavior arises from the recent necessity to find alternative propulsion systems, overcoming the range problems associated with fully electric vehicles. The innovation lies in the versatility and modularity of the model, which is open to modifications and features a low computational burden, making it suitable for testing new solutions by performing first design and sizing calculations.

Calibration Methodology and SiL Environment for Hybrid Powertrains

Calibration Methodology and SiL Environment for Hybrid Powertrains

Extending battery lifetime for electric wheel loaders with electric-hydraulic hybrid powertrain

Electrification is the future trend for construction machinery due to its advantage of zero-carbon emission. The battery of electric construction machinery has an inevitable degradation phenomenon, which will increase the maintenance cost. In this paper a parallel electric-hydraulic hybrid powertrain is proposed to extend battery lifetime of an electric wheel loader by utilizing a hydraulic powertrain to provide and capture power during launch and braking. Different operation modes are analyzed and a rule-based energy management strategy is developed to determine the holding and switching conditions of each mode. Powertrains and battery aging models are introduced in detail and dynamic simulation is developed in Simulink. Results show that the parallel electric-hydraulic hybrid powertrain with the proposed strategy can reduce the battery full equivalent cycles, thereby achieving a 15.64% improvement in the battery lifetime compared with the pure electric powertrain. Moreover, influences of the strategy parameters on extending the battery lifetime are further discussed, which gives a parametric design guideline to the energy management strategy.