Worldwide Harmonized Light Vehicles Test Cycle Research Articles

Ammonia Slip Estimation Based on Ammonia Slip Catalyst Control-Oriented Modeling and On-Board Diagnostics NOX Sensor Cross-Sensitivity Analysis

Abstract The incoming emission regulations for internal combustion engines are gradually introducing new pollutant species, which require greater complexity of the aftertreatment systems concerning layout, control, and diagnostics. This is the case of ammonia, which is injected into the exhaust gas through urea injections for NOx abatement in selective catalytic reduction (SCR) systems and can also be generated in three-way catalysts. However, ammonia slip requires its oxidation on a dedicated ammonia slip catalyst (ASC). The set composed of the urea injection system, SCR, and ASC requires control tools to ensure high NOx conversion efficiency and compliant ammonia slip under real driving conditions. These tasks are based on the use of NOx sensors ZrO2 pumping cell-based, which has the disadvantage of high cross-sensitivity to ammonia that can affect the measurement of NOx and compromise the SCR-ASC control strategies. The present work proposes a methodology to predict ammonia and NOx tailpipe emissions. For this purpose, a control-oriented ASC model was developed to use its ammonia slip prediction to determine the cross-sensitivity correction of the tailpipe NOx sensor. The model is based on a simplified solution of the transport equations of the species involved in the ASC reaction mechanism. The model was calibrated using steady- and quasi-steady-state tests performed in a Euro 6c engine. Finally, the performance of the proposed methodology to predict NOx and ammonia emissions was evaluated against experimental data corresponding to worldwide harmonized light vehicles test cycles (WLTC) applying different urea dosing strategies.

Heating performance of heat pump air conditioning system for battery electric vehicle with different refrigerants

To improve the heating performance of Heat Pump Air Conditioning System (HPACS) of Battery Electric Vehicle (BEV) and reduce the greenhouse effect of refrigerants, the performances of multiple refrigerants in different modes and conditions are analyzed in this paper. Based on Worldwide Harmonized Light Vehicles Test Cycle (WLTC) dynamic conditions, the impact of heating on battery State of Charge (SOC) is analyzed in HPACS and Positive Temperature Coefficient (PTC) combined heating mode. To better evaluate the contribution of refrigerants to the greenhouse effect, Total Equivalent Warming Impact (TEWI) is used to evaluate multiple refrigerants. The results show that heating capacity increases with the increment of compressor power and air velocity. As compressor power decreases and air velocity increases, COP increases. R32 and R744 are the optimal refrigerants. When the ambient temperature is between −10°C and −15°C under WLTC conditions, the SOC reduction of R32 system is 20.8%–21.1% less than that of R134a system. When the ambient temperature is between −20 and −25°C, the SOC reduction of R744 system is 21.4%–21.6% less than that of R134a system. And the carbon dioxide emissions of R32 and R744 systems are 35.1%, 66.9%, 39.2%, and 55.5% less than that of R134a system, respectively.

Model Development for State-of-Power Estimation of Large-Capacity Nickel-Manganese-Cobalt Oxide-Based Lithium-Ion Cell Validated Using a Real-Life Profile

This paper investigates the model development of the state-of-power (SoP) estimation for a 43 Ah large-capacity prismatic nickel-manganese-cobalt oxide (NMC) based lithium-ion cell with a thorough aging investigation of the cells’ internal resistance increase. For a safe operation of the vehicle system, a battery management system (BMS) integrated with SoP estimation functions is crucial. In this study, the developed SoP model used for the estimation of power throughout the lifetime of the cell is coupled with a dual-polarization equivalent-circuit model (DP_ECM) for achieving the precise estimation of desired parameters. The SoP model is developed based on the pulse-trained internal resistance evolution approach, and hence the power is estimated by determining the rate of internal resistance increase. Hybrid pulse power characterization (HPPC) test results are used for extraction of the impedance parameters. In the DP_ECM, Coulomb counting and extended Kalman filter (EKF) state estimation methods are developed for the accurate estimation of the state of charge (SoC) of the cell. The SoP model validation is performed by using both dynamic Worldwide harmonized Light vehicles Test Cycles (WLTC) and static current profiles, achieving promising results with root-mean-square errors (RMSE) of 2% and 1%, respectively.

Experimental study on combustion and emissions of a compression ignition engine fueled with gasoline

Gasoline compression ignition (GCI) is an effective way to achieve both high thermal efficiency and low emission. The combustion and emission performances of GCI and DCI (diesel compression ignition) were compared on a 2.0 L diesel engine equipped with Three-way catalyst-Lean NOx trap/Passive selective catalytic reduction (TWC-LNT/PSCR) aftertreatment system. In order to further clarify the advantages and disadvantages of GCI, this paper first studies the combustion and emission at 1500 rpm and braking average effective pressure (BMEP) of 4–9 bar. Secondly, six small map points of worldwide harmonized light vehicles test cycle (WLTC) are studied. The results show that the braking thermal efficiency (BTE) of GCI is lower than that of DCI at low load. When BMEP is greater than 5 bar, the BTE of GCI is significantly improved. GCI achieves a maximum BTE of 43%, which is 3% higher than DCI. Compared with DCI, the NOx emission of GCI is slightly lower, the smoke emission of filter smoke number (FSN) is significantly improved, and the CO and HC emissions are significantly increased. GCI engine equipped with TWC-LNT/PSCR system with high aftertreatment efficiency has the potential to meet China’s VI B emission regulations.

Emissions of Euro 6 Mono- and Bi-Fuel Gas Vehicles

Compressed natural gas (CNG) and liquefied petroleum gas (LPG) are included in the group of promoted transport fuel alternatives in Europe. Most studies on emissions factors are based on old technology CNG and LPG fueled vehicles. Furthermore, there are not many data at low ambient temperatures, on-road driving, or unregulated pollutants, such as ammonia (NH3). In this study we measured the emissions of one Euro 6b CNG light commercial vehicle, one Euro 6b and one Euro 6d-Temp bi-fuel LPG passenger car, one Euro 6d-Temp bi-fuel CNG passenger car, and four Euro 6d-Temp CNG passenger cars. Tests included on-road testing and worldwide harmonized light vehicles test cycles (WLTC) in the laboratory with cold and hot engine, at 23 °C and −7 °C. The results showed 10–23% CO2 savings in gas modality compared to gasoline, lower CO and particle number emissions, and relatively similar total and non-methane hydrocarbons and NOx emissions. The ammonia emissions were high for all vehicles and fuels; higher than gasoline and diesel vehicles. The results also showed that, following the introduction of the real-driving emissions regulation, even though not applicable to the examined vehicles, Euro 6d-Temp vehicles had lower emissions compared to the Euro 6b vehicles.

Numerical Assessment of Auto-Adaptive Energy Management Strategies Based on SOC Feedback, Driving Pattern Recognition and Prediction Techniques

The Equivalent Consumption Minimization Strategy (ECMS) is a well-known control strategy for the definition of optimal power-split in hybrid-electric vehicles, because of its effectiveness and reduced calibration effort. In this kind of Energy Management Systems (EMS), the correct identification of an equivalence factor (K), which translates electric power in equivalent fuel consumption, is of paramount importance. To guarantee charge sustaining operation, the K factor must be adjusted to different mission profiles. Adaptive ECMS (A-ECMS) techniques have thus been introduced, which automatically determine the optimal equivalence factor based on the vehicle mission. The aim of this research activity is to assess the potential in terms of fuel consumption and charge sustainability of different A-ECMS techniques on a gasoline hybrid-electric passenger car. First, the 0D vehicle and powertrain model was developed in the commercial CAE software GT-SUITE. An ECMS-based EMS was used to control the baseline powertrain and three alternative versions of an auto-adaptive algorithm were implemented on top of that. The first A-ECMS under study was based on feedback from the battery State of Charge, while the second and third on a Driving Pattern Recognition/Prediction algorithm. Fuel consumption was assessed using the New European Driving Cycle (NEDC), the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) and Real Driving Emissions (RDE) driving cycles by means of numerical simulation. A potential improvement of up to 4% Fuel Economy was ultimately achieved on an RDE driving cycle with respect to the baseline ECMS.

Impact of low carbon fuels (LCF) on the fuel efficiency and NOx emissions of a light-duty series hybrid commercial delivery vehicle

This work evaluates the potential of using four different low carbon fuels (LCF) in a series hybrid vehicle concept and compares the results to a conventional diesel combustion counterpart. To do this experimental data from a low NOx emission calibration is obtained for each of the different fuels, and 0-D vehicle simulations of an OPEL Movano van model are made to evaluate the performance, in terms of fuel consumption and engine-out NOx, during the Worldwide harmonized Light vehicles Test Cycles (WLTC) using a simplified engine map strategy. The vehicle selection allows to evaluate the scenario of a delivery application with three different payloads 0%, 50% and 100%. The work is motivated by the current automotive industry’s need to reduce emissions and use energy resources efficiently, evaluating different strategies to fulfil both objectives. The evaluation of different energy sources –such as LCF– and powertrains, have been extensively researched topics, however the information is more scarce using a combination of both strategies. The results from this work show that series hybrid vehicle presents a reduction of fuel consumption of up to 5% with 100% payload, across all fuels tested. Nonetheless, engine-out emission levels of NOx show 16% worse performance for the hybrid case due to its operation at higher engine speeds and loads during the charging of the battery.

Low-Temperature NO <sub>x</sub> Reduction by H <sub>2</sub> in Diesel Engine Exhaust

<div class="section abstract"><div class="htmlview paragraph">For the NO<sub>x</sub> removal from diesel exhaust, the selective catalytic reduction (SCR) and lean NO<sub>x</sub> traps are established technologies. However, these procedures lack efficiency below 200 °C, which is of importance for city driving and cold start phases. Thus, the present paper deals with the development of a novel low-temperature deNO<sub>x</sub> strategy implying the catalytic NO<sub>x</sub> reduction by hydrogen. For the investigations, a highly active H<sub>2</sub>-deNO<sub>x</sub> catalyst, originally engineered for lean H<sub>2</sub> combustion engines, was employed. This Pt-based catalyst reached peak NO<sub>x</sub> conversion of 95 % in synthetic diesel exhaust with N<sub>2</sub> selectivities up to 80 %. Additionally, driving cycle tests on a diesel engine test bench were also performed to evaluate the H<sub>2</sub>-deNO<sub>x</sub> performance under practical conditions. For this purpose, a diesel oxidation catalyst, a diesel particulate filter and a H<sub>2</sub> injection nozzle with mixing unit were placed upstream to the full size H<sub>2</sub>-deNO<sub>x</sub> catalyst. As a result, the Worldwide harmonized Light vehicles Test Cycle (WLTC), urban cycle segment of the Common Artemis Driving Cycle (CADC UC) and Transport for London Urban Inter Peak (TfL UIP) driving cycle revealed NO<sub>x</sub> conversions up to 90 % at temperatures as low as 80 °C. However, outside the low-temperature region, H<sub>2</sub>-deNO<sub>x</sub> activity dropped significantly evidencing the need for an additional underfloor SCR system. Moreover, slight N<sub>2</sub>O formation was observed in the engine tests making further catalyst development necessary, since N<sub>2</sub>O is considered a critical component due to its global warming potential. Additionally, the H<sub>2</sub> demand for low-temperature deNO<sub>x</sub> in diesel passenger cars was estimated and a novel on-board H<sub>2</sub> production strategy based on DEF electrolysis was developed. This method provided both H<sub>2</sub> as well as gaseous NH<sub>3</sub>. Subsequent simulations of H<sub>2</sub> production demonstrate small size factors (≤ 525 cm<sup>3</sup>) and rather low energy consumption of the H<sub>2</sub> supply unit, e.g. 0.25 kWh for the TfL UIP driving cycle.</div></div>

Quantitative study of vehicle CO2 emission at various temperatures and road loads

Vehicle CO2 emissions have been long studied, but the relationship between ambient temperature and CO2 emission has never been quantified. To quantitatively evaluate the correlation between ambient temperature and CO2 emission, two light-duty gasoline vehicles were tested over WLTC (Worldwide-harmonized Light vehicles Test Cycle) under four temperatures, −10 ℃, 0 ℃, 23 ℃, and 40 ℃. Obtained results proved that the dominant reason for the increased CO2 emission under cold ambient temperature is the increased internal resistance rather than fuel enrichments. CO2 emission from large engines is more sensitive to temperature variation while that from small engines are more sensitive to load variation. The usage of the air-conditioner increased the distance-specific CO2 emission by 23.07% and 22.49% for vehicle 1 and vehicle 2 respectively. The strong correlation (R2 greater than 0.98) between cumulated CO2 emission/coolant temperature and transient CO2 emission means the cumulated CO2 emission/coolant temperature could be used to describe the engine warm-up status and to improve the transient CO2 model. For the laboratory tests, using the coolant temperature to describe the engine warm-up needs more verification due to the uneven engine temperature field. This study helps understand the CO2 emission at various temperatures and the results in this study could be used for microscopic CO2 modeling & CO2-related regulations.

Study of a High-Efficiency Series–Parallel-Connected Hybrid-PM Variable-Flux Permanent Magnet Synchronous Machine

Variable-flux permanent magnet synchronous machines (PMSMs) are considered as a promising candidate in electric vehicle industry for their ability to operate in a wide speed range with high efficiency by manipulating the magnetization state dynamically. A novel high-efficiency series–parallel-connected hybrid-PM variable-flux PMSM is proposed in this article. The topology and operating principle are introduced. The performances, including magnetization/demagnetization ability, PM stability, and torque ability, are analyzed and compared with other hybrid-PM variable-flux PMSMs. The results show that the proposed machine retains the advantages and overcomes the limitations of the existing structures. The steady-state efficiency-maximizing magnetization state adjustment strategy is proposed and evaluated. The torque-speed range is expanded and the proportion of high-efficiency region increases obviously by using this strategy. The efficiency-maximizing magnetization state adjustment strategy considering magnetization state adjustment loss is proposed and evaluated with the worldwide harmonized light vehicles test cycle (WLTC). The efficiency during the whole driving circle is significantly improved by adopting the proposed strategy.

Development of semi-empirical soot emission model for a CI engine

Soot is one of the main harmful emissions of diesel engines that is mainly generated in the reacting fuel jet of diesel injection. Over 99% of the engine-out soot can be filtered by a diesel particulate filter (DPF). However, when the soot load of the DPF is high, a regeneration process that oxidizes the accumulated soot reduces fuel economy. A real-time soot estimation model can contribute to real-time feedback soot control under transient conditions to minimize the engine-out soot emission and frequency of DPF regeneration.A zero-dimensional engine-out soot estimation model for a diesel engine is developed in this study. The semi-empirical soot model considers both the formation and oxidation of soot. In the model, soot formation was correlated with the cross-sectional average equivalence ratio at the lift-off length of the fuel spray. The equivalence ratio at the lift-off length is an indicator of how much air and vaporized fuel are mixed as the fuel reaches the reaction zone. The mass of the injected fuel and combustion duration were also correlated with soot formation. The Nagle and Strickland-Constable mechanism, which calculates the soot oxidation rate was correlated with the soot oxidation in this study. The results of the soot estimation showed an R2 of 0.901 and root mean square error of 10.8 mg/m3 for steady-state experimental cases. The engine-out soot model was also combined with the in-cylinder pressure model proposed by the authors, and validated through the transient Worldwide Harmonized Light Vehicles Test Cycle (WLTC) mode. The estimates agreed with the measured soot, with an accumulated soot error of approximately 6% during the WLTC, even without using an in-cylinder pressure sensor. The soot model developed in this study can help minimize tailpipe-out soot emissions and improve fuel economy by influencing the real-time feedback control during transient and frequent DPF regeneration.

Development of prediction methodology for CO2 emissions and fuel economy of light duty vehicle

Fuel economy prediction models usually require vehicle specifications such as a fuel consumption map which are not publicly available. Therefore, the present study proposed a new data analyzing procedure to predict CO2 emissions and fuel economy using on-road driving data without confidential specifications. Vehicle specifications such as gear ratios and vehicle mass which are provided in a service manual and driving data such as vehicle speed and CO2 emission were used to develop the prediction model. Instead of the fuel consumption map, linear equations for each gear between wheel power and CO2 emissions were used to predict CO2 emissions for various driving modes. Since higher gears exhaust less CO2 than lower gears (the seventh gear exhausted 24.4% less CO2 than the first gear), the accuracy of fuel economy prediction was improved by applying the equations for each gear stage. The accuracy of the prediction was verified by comparing it with measurement data. The comparisons showed that the equations for each gear can predict the fuel economy more accurately than one equation representing the entire gear. In worldwide harmonized light vehicles test cycle (WLTC) mode, the former had a maximum error of 6.1%, but the latter showed an error of 17.9%.

Impact of Electric Heating Catalyst on the Emissions for a 48V Hybrid Light-duty Vehicle

The emission characteristics under worldwide harmonized light vehicles test cycle (WLTC) was investigated for a 48V hybrid light-duty vehicle which carried a 2.0 L naturally aspirated engine on engine test bed after the WLTC cycle was converted to the corresponding engine transient cycle. The influence of electric heating catalyst on exhaust emission was analyzed. The results show that electric heating catalyst can effecively speed up the temperature rise rate then significantly decreases the exhaust emission. Electric heating has a more pronounced effect for ceramic carrier catalyst.

Effectiveness of the measures for CO2 emission reduction in real world

To reduce the CO2 emission level for the new Corporate Average Fuel Economy regulations, a series of measures are implemented by the manufacturers. Besides the use of hybrid and electric vehicles, efficiencies packages are frequently applied to improve the CO2 emissions of conventional vehicles. Some examples of CO2 reduction measures are: Start&Stop system, eco tires, powertrain thermal management and aerodynamic kits. Usually, they are optimized for the WLTC (Worldwide Harmonized Light Vehicles Test Cycle). The aim of this paper is to assess the influence of these packages in real-world driving cycles. The study is done by means of modelling and simulation, using an industrial modelling and simulation environment (LMS Imagine.Lab AMESim). Two passenger cars from different classes, a compact type and a SUV are used.

Real-Time Emission Prediction with Detailed Chemistry under Transient Conditions for Hardware-in-the-Loop Simulations

The increasing requirements to further reduce pollutant emissions, particularly with regard to the upcoming Euro 7 (EU7) legislation, cause further technical and economic challenges for the development of internal combustion engines. All the emission reduction technologies lead to an increasing complexity not only of the hardware, but also of the control functions to be deployed in engine control units (ECUs). Virtualization has become a necessity in the development process in order to be able to handle the increasing complexity. The virtual development and calibration of ECUs using hardware-in-the-loop (HiL) systems with accurate engine models is an effective method to achieve cost and quality targets. In particular, the selection of the best-practice engine model to fulfil accuracy and time targets is essential to success. In this context, this paper presents a physically- and chemically-based stochastic reactor model (SRM) with tabulated chemistry for the prediction of engine raw emissions for real-time (RT) applications. First, an efficient approach for a time-optimal parametrization of the models in steady-state conditions is developed. The co-simulation of both engine model domains is then established via a functional mock-up interface (FMI) and deployed to a simulation platform. Finally, the proposed RT platform demonstrates its prediction and extrapolation capabilities in transient driving scenarios. A comparative evaluation with engine test dynamometer and vehicle measurement data from worldwide harmonized light vehicles test cycle (WLTC) and real driving emissions (RDE) tests depicts the accuracy of the platform in terms of fuel consumption (within 4% deviation in the WLTC cycle) as well as NOx and soot emissions (both within 20%).

Developing local driving cycle for accurate vehicular CO2 monitoring: A case study of Tehran

Driving cycles used in legislation are fixed schedules of vehicle operation for standard emission evaluation of different vehicles. Recently, the growing deviation of CO2 values obtained with standard driving cycles from those recorded in real driving has prompted the development of new driving cycles to better estimate CO2 emission. International Council of Clean Transportation (ICCT) reports about a 40% deviation when vehicles are tested under New European Driving Cycle (NEDC). The introduction of Worldwide harmonized Light vehicles Test Cycles (WLTC) has reduced the gap between lab and road to 20%. However, this gap is predicted to grow until more robust tests based on real driving emissions (RDE) are presented for 2025 and beyond. This growing gap is a significant concern for reducing the carbon footprint in the transport section. The present article discusses developing local driving cycles for reducing this gap in passenger vehicles. Two distinct cycles with a good approximation of real driving were developed using the k-means clustering method. The CO2 emission of a 5-door passenger vehicle in these cycles was estimated using computer simulation. Compared with NEDC and WLTC, 30% less deviation from average CO2 emission levels recorded in real driving profiles was obtained with generated local driving cycles. The benefits of local driving cycles in legislation and reaching interim targets in reducing carbon emissions were discussed. The authors suggested implementing local driving cycles in type approvals without robust procedures based on real driving emissions. Granting subsidies to vehicles complying with local type approvals is also suggested as a stimulating policy for car manufacturers to boost overseas markets. It is concluded that replacing legislative driving cycles used for emission estimation with local driving cycles can significantly improve carbon reduction before implementing RDE into legislation.

Comparative study on fuel saving potential of series-parallel hybrid transmission and series hybrid transmission

The series hybrid transmission (SHT) and series-parallel hybrid transmission (SPHT) have become an important development direction in the field of hybrid electric vehicles (HEVs) in China. The main difference between a SHT and SPHT is that the engine can directly drive the vehicle through the addition of one clutch in the SPHT. The SPHT is thus more complex in structure, but its fuel economy advantages, as compared with the SHT, have remained controversial. Therefore, this study provides a thorough comparison between the SHT and SPHT for different types of vehicles and driving cycles. A global optimal control strategy based on dynamic programming (DP) is developed to evaluate the economic performance of the SHT and SPHT. Particularly, a mode-switching penalty matrix is designed in the control strategy based on the energy consumed during the mode-switching process. To exclude the influence of the configuration parameters and power sources, a large number of simulations are conducted for different parameter combinations. The results show that the SPHT has notable advantages in fuel saving compared with the SHT, especially in high-speed driving cycles for type C vehicles, while there is a negligible difference in the fuel consumption between the two for type A vehicles under urban driving cycles. Under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC), the SPHT has a fuel saving of approximately 7.2% more than the SHT for type B vehicles. This study provides a new theoretical basis on technical path selection for the SHT and SPHT.

Optimal Integrated Emission Management through Variable Engine Calibration

In this work, the potential for improving the trade-off between fuel consumption and tailpipe NOx emissions through variable engine calibration (VEC) is demonstrated for both conventional and hybrid electric vehicles (HEV). First, a preoptimization procedure for the engine operation is proposed to address the challenge posed by the large number of engine control inputs. By excluding infeasible and suboptimal operation offline, an engine model is developed that can be evaluated efficiently during online optimization. Next, dynamic programming is used to find the optimal trade-off between fuel consumption and tailpipe NOx emissions for various vehicle configurations and driving missions. Simulation results show that for a conventional vehicle equipped with VEC and gear optimization run on the worldwide harmonized light vehicles test cycle (WLTC), the fuel consumption can be reduced by 5.4% at equivalent NOx emissions. At equivalent fuel consumption, the NOx emissions can be reduced by 80%. For an HEV, the introduction of VEC, in addition to the optimization of the torque split and the gear selection, drastically extended the achievable trade-off between fuel consumption and tailpipe NOx emissions in simulations. Most notably, the region with very low NOx emissions could only be reached with VEC.

Studies on Energy Consumption of Electric Light Commercial Vehicle Powered by In-Wheel Drive Modules

This article presents the results of energy consumption research for an electric light commercial vehicle (eLCV) powered by a centrally located motor (4 × 2 drive system) or motors placed in the vehicle’s wheels (4 × 4 drive system). For the considered constructions of electric drive systems, mathematical models of 4 × 2 and 4 × 4 drive systems were developed in the Modelica simulation environment, based on real data. Additionally, the influence of changes in the vehicle loading condition on the operation of the motor mounted in the wheel and the energy consumption of the drive module was investigated. On the basis of the conducted research, a comparative analysis of energy consumption by electric drive systems in 4 × 2 and 4 × 4 configurations was carried out for selected test cycles. The tests carried out with the Worldwide harmonized Light vehicles Test Cycles (WLTC) test cycle showed a roughly 6% lower energy consumption by the 4 × 4 drive system compared to the 4 × 2 configuration.

Analysis of a Hybrid Permanent Magnet Variable-Flux Machine for Electric Vehicle Tractions Considering Magnetizing and Demagnetizing Current

The overall driving cycle efficiency of conventional permanent magnet synchronous machines (PMSMs) for electric vehicle tractions in a wide speed range is constrained due to the large field weakening current and high iron loss in high speed. The series hybrid permanent magnet variable flux machines (HPM-VFMs) which employ both low coercive force (LCF) magnets and high coercive force magnets are proposed to obtain high torque density and flexible air-gap flux density simultaneously. The key of HPM-VFMs design is the accuracy of hysteresis model of LCF magnets and operating principle analysis. This article contributes to clarify operating principle based on hysteresis model of AlNiCo magnets and propose a novel design consideration to reduce magnetizing and demagnetizing current. Based on the theoretical analysis, this article proposes a novel series HPM-VFM, in which the NdFeB and AlNiCo magnets are arranged separately. Furthermore, flux paths are designed to achieve appropriate interaction between two kinds of magnets. The proposed machine has features of wide magnetization state (MS) variation range, low magnetizing and demagnetizing current, and low risk of unintentional demagnetization. By manipulating the MS of the proposed machine, the losses of a wide speed range operation could be reduced. The comparison of efficiency maps and the worldwide-harmonized light vehicles test cycle driving cycle losses between the proposed machine and a conventional interior PMSM proves that the proposed machine achieves higher efficiency for electric vehicle.