Driving Cycle Conditions Research Articles

Measurement of particulate polycyclic aromatic hydrocarbon emissions from gasoline light-duty passenger vehicles

Abstract Tackling vehicle emissions is one important task for governmental stakeholders to develop cleaner cities. Gasoline-fueled light-duty passenger vehicles (LDPVs) are intensively used in populous urban areas to meet passenger transportation demand. However, gasoline vehicle emissions raise the health risk due to the proximity of exposure to gasoline exhaust. To better understand the genotoxicity of gasoline emissions, this study is focused on their emissions of particulate polycyclic aromatic hydrocarbons (p-PAHs). We combined dynamometer testing, filter sampling and offline chemical analysis to measure p-PAH emissions from five in-use gasoline LDPVs. The results indicate that the emission factors of tested vehicles under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) decrease significantly with emission standard, from 11.27 μg km−1 for one China 3 LDPV to below 6 μg km−1 for the other newer LDPVs (China 4 and 5). Different from the mass distribution of p-PAH species for diesel vehicles, medium-and high-molecular-weight PAHs (e.g., 4, 5, and 6-ring species) are considerably identified from the gasoline particle samples. These medium and high-weight PAHs, such as benzo [a]pyrene (BaP) and dibenzo [ah]anthracene (DaA), in general have much greater toxic equivalency factors than low-molecular-weight PAHs. Furthermore, this study also reports that engine type and driving cycle conditions would have discernible impacts on p-PAH emissions. The gasoline direct injection (GDI) engine-equipped LDPVs would increase p-PAH emissions compared with the counterparts using port-fuel injection (PFI) engines. Cold start and transient driving conditions could also result in increased p-PAH emissions, while high-speed driving conditions tend to reduce the p-PAH content in total particles. The significant health impacts caused by p-PAH emissions from gasoline LDPVs should be concerned, and more effective measures should be taken to eliminate gasoline particle emissions.

Adaptive Fuzzy Sliding Mode Observer for Cylinder Mass Flow Estimation in SI Engines

In this paper, a novel algorithm for the cylinder mass flow estimation in four-stroke spark ignition (SI) gasoline engines is developed to improve the estimation precision under transient conditions. The error of the cylinder mass flow is compensated by the error variable of the volumetric efficiency caused by the calibration errors and ambient changes. Since the volumetric efficiency error in SI gasoline engines is dependent on the intake manifold pressure, engine speed, and ambient temperature, a fuzzy logic system (FLS) with three inputs is adopted to parameterize the volumetric efficiency error. With the combination of the FLS and the gasoline engine air path system, an adaptive fuzzy sliding mode observer is presented to estimate the states and parameters jointly and suppress the disturbance from the FLS approximation error. With the conditions of persistent excitation and the given inequality, the convergence of the proposed method is proven. The performance of the proposed method is validated in the environment of a R4-cylinder SI gasoline engine from enDYNA during different driving-cycle conditions, demonstrating that the estimation precision of the cylinder air inflow can be obviously improved by the proposed algorithm under transient conditions.

Machine learning an alternate technique to estimate the state of charge of energy storage devices

State of charge (SOC) estimation plays a critical role in the operation of an electric vehicle (EV) power battery. In this Letter, the authors propose machine learning (ML) algorithms as alternate to the existing filtering algorithms used for SOC estimation of an EV battery. The SOC estimation approach is evaluated by the simulation experiments in advanced vehicle simulator (ADVISOR). For the modelling of ML algorithms, the input parameters that affect the SOC estimation are battery current, battery module temperature, power out of the battery (available and requested), battery power loss and heat removed from the battery. Training and testing stages of the models are carried out using the data collected from ADVISOR. As the drive cycle conditions provided by ADVISOR are universal therefore present method is applicable to all kinds of batteries used in EVs including lithium ion, nickel metal hydride and lead acid batteries. Thus, the proposed models for SOC estimation provide an alternative approach in SOC estimation.

Parameter Identification of Electrochemical Model for Vehicular Lithium-Ion Battery Based on Particle Swarm Optimization

The dynamic characteristics of power batteries directly affect the performance of electric vehicles, and the mathematical model is the basis for the design of a battery management system (BMS).Based on the electrode-averaged model of a lithium-ion battery, in view of the solid phase lithium-ion diffusion equation, the electrochemical model is simplified through the finite difference method. By analyzing the characteristics of the model and the type of parameters, the solid state diffusion kinetics are separated, and then the cascade parameter identifications are implemented with Particle Swarm Optimization. Eventually, the validity of the electrochemical model and the accuracy of model parameters are verified through 0.2–2 C multi-rates battery discharge tests of cell and road simulation tests of a micro pure electric vehicle under New European Driving Cycle (NEDC) conditions. The results show that the estimated parameters can guarantee the output accuracy. In the test of cell, the voltage deviation of discharge is generally less than 0.1 V except the end; in road simulation test, the output is close to the actual value at low speed with the error around ±0.03 V, and at high speed around ±0.08 V.

Start-Stop Moment Optimization of Range Extender and Control Strategy Design for Extended -Range Electric Vehicle

Range extender is the core component of E-REV, its start-stop control determines the operation modes of vehicle. This paper based on a certain type of E-REV, researched constant power control strategy of range extender in extended-range model, to target range as constraint condition, combined with different driving cycle conditions, by correcting battery SOC for range extender start-stop moment, optimized the control strategy of range extender, and established the vehicle and range extender start-stop control simulation model. Selected NEDC and UDDS conditions simulation results show that: under certain target mileage, the range extender running time reduced by 37.2% and 28.2% in the NEDC condition, and running time UDDS conditions were reduced by 40.6% and 33.5% in the UDDS condition, reached the purpose of meeting the vehicle mileage and reducing consumption and emission.

Performance evaluation of a PEM fuel cell stack with variable inlet flows under simulated driving cycle conditions

Alongside battery, polymer electrolyte membrane (PEM) fuel cell stack has been a promising candidate asa power source for hybrid and electric vehicles. On this application, the dynamic performance of the PEM fuel cell is crucial in ensuring smooth operation of the vehicle. The PEM fuel cell stack should be maintained at its optimum performance while being responsive during real road driving condition which is best represented by legislative driving cycle. The present study is conducted to evaluate the performance of a PEM fuel cell stack for vehicle application subjected to New European Driving Cycle (NEDC) by utilizing computational fluid dynamics (CFD) approach. The studied PEM fuel cell stack comprises 320 cells with 1600 cm2 active catalyst area. The effect of variable inlet following NEDC profile on the PEM fuel cell performance is investigated as well. Several possible scenarios, i.e. steady inlet flows, variable inlet flows at anode, cathode, coolant and combinations of these, are examined and discussed in the light of numerical result. The results reveal that variable inlet flows have considerable effect on the total net power generated, thermal envelope and liquid saturation albeit its marginal effects on the stack performance in term of stack power.

(Invited Plenary) Durability of Polymer Electrolyte Membrane Fuel Cells and the Development of Accelerated Stress Tests

The durability of Polymer Electrolyte Membrane Fuel Cells (PEMFCs) is one of the key barriers to their commercialization in automotive applications.1 All the components of the fuel cell membrane electrode assembly (MEA) including the catalyst, catalyst support, membrane and Gas diffusion layers have shown degradation during fuel cell operation. The DOE – Fuel Cell Technologies program has set lifetime durability targets of 5000 hours for automotive fuel cells and the U.S. Drive Fuel Cell Technical Team (FCTT) has developed AST protocols for the various components.2 This talk will outline the degradation mechanisms that have been observed in MEA components, and detail the Accelerated Stress Tests that have been designed to evaluate these degradation modes. The major degradation mechanism observed with Pt-alloy catalysts is the leaching of the transitional metal from the Pt –alloy and the associated mass activity loss. This is in contrast to pure Pt-catalyst where the main degradation mechanism is the increase of average catalyst particle size and associated loss in surface area. While most alloy catalysts also exhibit increase in particle size, the voltage loss in fuel cells is primarily controlled by the de-alloying of the catalyst. XRD and TEM studies reveal that the transition metal is seen to migrate out of the catalyst nano-particle into the ionomer within the catalyst layer and membrane. This mechanism has been observed during both simulated drive cycle measurements and AST measurements. Data will be presented from 2 different ASTs. The older FCTT AST that consists of potential cycling from 0.6 V to 1.0 V at 50 mV/sec3 and a newer electro-catalyst AST which is a square wave with upper and lower potentials of 0.95 V and 0.6 V with 3 seconds duration, and was based on literature reports.4 The degradation in these ASTs will be compared to that observed while performing the durability drive cycle protocol recommended by the FCTT.2 The Pt catalyst is usually supported on carbon that provides porosity and electronic conductivity to the catalyst layer. However, this carbon has been observed to corrode at high potentials. This corrosion either results in the evolution of CO2 and depletion of carbon in the catalyst layer or to an increase in oxide surface groups on the carbon and associate increase in hydrophilicity. Results from carbons with different surface areas will be presented and fuel cell performance loss will be correlated to both the collapse of the pore structure in the catalyst layer and the increasing platinum particle size resulting from support corrosion. CO2 evolution data will be presented to quantify the amount of carbon corrosion during drive cycle and AST measurements. Carbon corrosion during start/stop measurements and its effect on fuel cell performance will also be presented. Global and local membrane thinning due to chemical and mechanical degradation respectively have been observed during fuel cell operation. Data from field tests (Busses operated by Ballard) and drive cycle testing have shown that local failure primarily happens due to mechanical degradation which is further accelerated by any chemical degradation. The performance of un-stabilized and stabilized (both mechanical and chemical) membranes will be presented. The fluorine emission from the membranes is a good estimate of degradation rates and is accelerated by hot, dry conditions at open circuit and by RH cycling. A combined mechanical/chemical AST (RH cycling at OCV) was developed to mimic membrane durability under drive cycle conditions. Finally gas diffusion layer degradation and its effect on fuel cell performance will be presented. Drive cycle tests performed with Sigracet 24BC GDLs exhibited mass transport losses consistent with GDL degradation. This degradation was completely mitigated with the use of more advanced GDLs including Sigracet 29BC.

Energy Optimization for a Weak Hybrid Power System of an Automobile Exhaust Thermoelectric Generator

An integrated starter generator (ISG)-type hybrid electric vehicle (HEV) scheme is proposed based on the automobile exhaust thermoelectric generator (AETEG). An eddy current dynamometer is used to simulate the vehicle’s dynamic cycle. A weak ISG hybrid bench test system is constructed to test the 48 V output from the power supply system, which is based on engine exhaust-based heat power generation. The thermoelectric power generation-based system must ultimately be tested when integrated into the ISG weak hybrid mixed power system. The test process is divided into two steps: comprehensive simulation and vehicle-based testing. The system’s dynamic process is simulated for both conventional and thermoelectric powers, and the dynamic running process comprises four stages: starting, acceleration, cruising and braking. The quantity of fuel available and battery pack energy, which are used as target vehicle energy functions for comparison with conventional systems, are simplified into a single energy target function, and the battery pack’s output current is used as the control variable in the thermoelectric hybrid energy optimization model. The system’s optimal battery pack output current function is resolved when its dynamic operating process is considered as part of the hybrid thermoelectric power generation system. In the experiments, the system bench is tested using conventional power and hybrid thermoelectric power for the four dynamic operation stages. The optimal battery pack curve is calculated by functional analysis. In the vehicle, a power control unit is used to control the battery pack’s output current and minimize energy consumption. Data analysis shows that the fuel economy of the hybrid power system under European Driving Cycle conditions is improved by 14.7% when compared with conventional systems.

Adaptive Model Predictive Control-Based Energy Management for Semi-Active Hybrid Energy Storage Systems on Electric Vehicles

This paper deals with the energy management strategy (EMS) for an on-board semi-active hybrid energy storage system (HESS) composed of a Li-ion battery (LiB) and ultracapacitor (UC). Considering both the nonlinearity of the semi-active structure and driving condition uncertainty, while ensuring HESS operation within constraints, an adaptive model predictive control (AMPC) method is adopted to design the EMS. Within AMPC, LiB Ah-throughput is minimized online to extend its life. The proposed AMPC determines the optimal control action by solving a quadratic programming (QP) problem at each control interval, in which the QP solver receives control-oriented model matrices and current states for calculation. The control-oriented model is constructed by linearizing HESS online to approximate the original nonlinear model. Besides, a time-varying Kalman filter (TVKF) is introduced as the estimator to improve the state estimation accuracy. At the same time, sampling time, prediction horizon and scaling factors of AMPC are determined through simulation. Compared with standard MPC, TVKF reduces the estimation error by 1~3 orders of magnitude, and AMPC reduces LiB Ah-throughput by 4.3% under Urban Dynamometer Driving Schedule (UDDS) driving cycle condition, indicating superior model adaptivity. Furthermore, LiB Ah-throughput of AMPC under various classical driving cycles differs from that of dynamic programming by an average of 6.5% and reduces by an average of 10.6% compared to rule-based strategy of LiB Ah-throughput, showing excellent adaptation to driving condition uncertainty.

Transient structural and catalytic behaviour of Pt-particles probed by operando spectroscopy during a realistic driving cycle

Pt catalysts investigated with operando XAS under rapid transient temperature automotive driving cycle conditions.

Overall efficiency optimization of controllable mechanical turbo-compounding system for heavy duty diesel engines

A controllable mechanical turbo-compounding (CMTC) system including continuously variable transmission (CVT) and power turbine bypass valve is proposed to recover waste heat from engine exhaust. The combined matching principle considering swallowing capacity of both charging turbine and power turbine, main gear ratio is investigated at first based on the analysis of individual influence. Then the effects and strategies of CVT and power turbine bypass valve are studied for better performance under off-design conditions. At last, the transient response of intake pressure of engine with CMTC system is researched and the fuel saving potential is tested under driving cycle conditions. The results indicate that the overall fuel efficiency elevates at the off-design conditions if CVT is adopted due to the improvement of power turbine operating efficiency by speed modulation. The diversion of exhaust through power turbine bypass valve under the low load condition is necessary. The back pressure of the charging turbine infuences the transient response of intake pressure for a fixed CMTC configuration. A method featured by the assistance of power turbine bypass valve is tested to improve the transient response of the intake pressure. The fuel consumption reduces by 2% and 3.4% under highway fuel economy test (HWFET) and Tianjin 503 (TJ503) driving cycles respectively.

A model-predictive-control-based power management strategy for a power-split electromechanical transmission

A power management strategy is a key necessity for power-split electromechanical transmission systems. A model predictive control strategy which is based on finite-horizon optimization and can combine the advantages of instantaneous optimization and global optimization is a good solution for online optimization of the power management. Therefore, a model-predictive-control-based power management strategy is proposed for a two-mode electromechanical transmission. A model predictive control strategy consists of two parts: a predictive model and a receding-horizon optimization algorithm. A predictive model is used for predicting future information on the electromechanical transmission states, and real-time receding-horizon optimization with a finite horizon is adopted for optimal decision making. First, the predictive model, including the battery state and the transmission output torque, which provides a priori knowledge for optimal calculation, is proposed. Then, to ensure optimal operating areas of the engine and the motors, a novel overall efficiency calculation method for the whole powertrain including the engine, the motors, the power-split coupled machine and the battery is proposed and regarded as the optimization objective. The overall efficiency not only is focused on the engine fuel economy but also determines the power loss of the motors, the battery and the planetary gears together, which enhances the fuel economy and the transmission efficiency significantly. Based on the predictive model and receding-horizon optimization, the MPC strategy is established and tested by hardware-in-the-loop simulations under Urban Dynamometer Driving Schedule and New European Driving Cycle conditions. The test results showed that the power management strategy can enhance the fuel economy and proved to be a potential real-time optimization method for power distribution in the electromechanical transmission system; this strategy can provide theoretical support for actual application of electromechanical transmission systems.

Characterization and Modeling of a Hybrid-Electric-Vehicle Lithium-Ion Battery Pack at Low Temperatures

Although lithium-ion batteries have penetrated hybrid electric vehicles (HEVs) and pure electric vehicles (EVs), they suffer from significant power capability losses and reduced energy at low temperatures. To evaluate those losses and to make an efficient design, good models are required for system simulation. Subzero battery operation involves nonclassical thermal behavior. Consequently, simple electrical models are not sufficient to predict bad performance or damage to systems involving batteries at subzero temperatures. This paper presents the development of an electrical and thermal model of an HEV lithium-ion battery pack. This model has been developed with MATLAB/Simulink to investigate the output characteristics of lithium-ion batteries over the selected operating range of currents and battery capacities. In addition, a thermal modeling method has been developed for this model so that it can predict the battery core and crust temperature by including the effect of internal resistance. First, various discharge tests on one cell are carried out, and then, cell's parameters and thermal characteristics are obtained. The single-cell model proposed is shown to be accurate by analyzing the simulation data and test results. Next, real working conditions tests are performed, and simulation calculations on one cell are presented. In the end, the simulation results of a battery pack under HEV driving cycle conditions show that the characteristics of the proposed model allow a good comparison with data from an actual lithium-ion battery pack used in an HEV.

Evaluation of the time-resolved nanoparticle emissions and the vehicle performance characteristics for a turbocharged gasoline direct-injection vehicle with a metal-foam gasoline particulate filter

The nanoparticle emissions from gasoline direct-injection engines are of concern because of the high particle number concentrations compared with those from a gasoline port fuel injection engine. A gasoline particulate filter is a potential solution for reducing the particulate matter emissions. In this study, a 2.0 l turbocharged gasoline direct-injection vehicle with a metal-foam-type gasoline particulate filter was tested using the New European Driving Cycle and steady vehicle operating conditions. The particle number concentration, the particle-size distribution and the filtration efficiency were determined using a condensation particle counter and a fast response differential mobility spectrometer (DMS500). The particle number emissions (particle numbers per vehicle travelling distance (particles/km)) over the New European Driving Cycle were 1.95 × 1012 particles/km for a base vehicle equipped with a three-way catalytic converter and 5.68 × 1011 particles/km for the additional installation of a gasoline particulate filter on the base gasoline direct-injection vehicle. The filtration efficiency of the particle number and the particulate matter mass reached approximately 71% and 67% respectively. The nucleation-mode particles in the size range less than 23 nm for the gasoline direct-injection vehicle equipped with a three-way catalytic converter were further reduced on installation of a gasoline particulate filter at the downstream position of the three-way catalytic converter. A sharp pressure drop between the gasoline particulate filter of 21.0 mbar was obtained at a vehicle speed of 120 km/h in the New European Driving Cycle. The exhaust gas temperature before the gasoline particulate filter reached around 380–610 °C at steady vehicle speeds of 60–120 km/h. The installation of the gasoline particulate filter has the potential to satisfy the Euro 6c particle number emissions regulations for light-duty gasoline direct-injection vehicles.

Reduced Order Modeling of Mechanical Degradation Induced Performance Decay in Lithium-Ion Battery Porous Electrodes

A one-dimensional computational framework is developed that can solve for the evolution of voltage and current in a lithium-ion battery electrode under different operating conditions. A reduced order model is specifically constructed to predict the growth of mechanical degradation within the active particles of the carbon anode as a function of particle size and C-rate. Using an effective diffusivity relation, the impact of microcracks on the diffusivity of the active particles has been captured. Reduction in capacity due to formation of microcracks within the negative electrode under different operating conditions (constant current discharge and constant current constant voltage charge) has been investigated. At the beginning of constant current discharge, mechanical damage to electrode particles predominantly occurs near the separator. As the reaction front shifts, mechanical damage spreads across the thickness of the negative electrode and becomes relatively uniform under multiple discharge/charge cycles. Mechanical degradation under different drive cycle conditions has been explored. It is observed that electrodes with larger particle sizes are prone to capacity fade due to microcrack formation. Under drive cycle conditions, small particles close to the separator and large particles close to the current collector can help in reducing the capacity fade due to mechanical degradation.

An instantaneous optimization strategy based on efficiency maps for internal combustion engine/battery hybrid vehicles

This paper presents an instantaneous optimization algorithm based on the knowledge of the efficiency maps of the internal combustion engine (ICE) and the generator for the energy management system in hybrid electric vehicles. The proposed method formulates a new cost function representing the analytical expression of the overall energy efficiency of the hybrid energy source (i.e. ICE/generator set+battery pack) which is calculated based on the energy flow at the DC bus. Engine operating points are determined by assessing not only the efficiency map of the engine but also the efficiency map of the generator and the charge/discharge efficiency of the battery pack in order to maximize the efficiency of the energy delivered from the hybrid energy source to the drive system. The performance of the proposed method is analyzed and demonstrated on a hybrid electric bus developed in MATLAB/Simulink for different driving cycle conditions and the results have been compared with alternative optimization methods such as equivalent consumption minimization strategy (ECMS), model predictive control (MPC) and dynamic programming (DP) approach. The simulation results show that the proposed method provides a competitive performance with a lower computational burden compared to the alternative methods for different state of charge (SOC) ranges and drive cycle conditions.

Pollutants emission and particle behavior in a pre-turbo aftertreatment light-duty diesel engine

Diesel particulate filters are a standard technology used in diesel engines in order to comply with actual and forthcoming regulations, regarding soot emissions and particulate matter in exhaust gases. In recent years, pre-turbo aftertreatment response has been investigated as opposed to the traditional aftertreatment location downstream from the turbine but just regarding engine performance. Previous studies do not deal in detail with gaseous and particle emission analysis in a pre-turbo aftertreatment configuration. This paper focuses on these topics. The gaseous and particle emissions have been assessed in a 4-cylinder, light-duty diesel EURO 4 engine typically used in European passenger car vehicles. Different steady-state operating points have been considered in order to extend the study over a wide range of operating conditions. Additionally, the New European Driving Cycle has been performed with the aim of reaching a comprehensive understanding of the aftertreatment dynamic response in terms of pollutant emissions. An increase in the amount of NO2 converted from NO and a reduction in emitted CO have been found at low load steady-state operating conditions with pre-turbo aftertreatment placement. In driving cycle conditions, a shift from nucleation to accumulation mode particles have been found, being the filtration efficiency scarcely affected.

MIMO H∞ control for power source coordination – application to energy management systems of electric vehicles

This paper deals with a control strategy used for designing energy management systems within average-power electric vehicles. The power supply system is composed of three sources, namely a fuel cell, a battery and an ultracapacitor – specialized within distinct frequency ranges – which must be coordinated in order to satisfy power demand of the vehicle's electrical motor. The three sources with their associated DC-DC converters are paralleled on a common DC-bus supplying the electrical motor. The DC-bus is required to be constant regardless of the load state thanks to the fuel cell which provides the mean power and to the other two sources – auxiliary sources – which are controlled to supply the high-frequency variations of power demand according to an H∞ optimization strategy. MATLAB®/Simulink® numerical simulation is used to validate the proposed strategy under real driving cycle condition proposed by IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux), and this approach is assessed against another optimal strategy that uses LQR as control design.

Two-Speed DCT Electric Powertrain Shifting Control and Rig Testing

Dual clutch transmissions (DCTs) are recognized as being suitable for electric drive applications as they can drive with high efficiency and achieve good shifting comfort. A two-speed DCT electric drivetrain is described in this paper, comprised of only two gear pairs and a final drive gear in the two-speed gearbox. The fundamental shifting control algorithm is provided. On the testing rig of University of Technology, Sydney (UTS) powertrain lab, shifting controls and some driving cycle controls were realized. The results demonstrated that the control algorithm functioned well both in transient shifting control process and in the driving cycle conditions.

Design and Simulation of Pure Electric Vehicle Power System

According to pure electric vehicle dynamic requirements and the driving conditions, took an electric vehicle as an example, analyzed principle and method of power system with voltage, electric current, capacity and connection methods. Software ADVISOR was employed to establish vehicle model, analyzed dynamic performance under drive cycle conditions. Simulation result indicate that battery pack is in normal state, dynamic performances including acceleration performance, gradient ability, maximum speed, driving mileage are satisfied to design requirements. So the rationality and validity of the power system are demonstrated.