Toyota Prius Hybrid Electric Vehicle Research Articles

Particle Number and Size Distributions (PNSD) from a Hybrid Electric Vehicle (HEV) over Laboratory and Real Driving Emission Tests

Particle number (PN) emissions from hybrid electric vehicles (HEV) during engine ignition and re-ignition events are an important but scarcely reported area. The objectives of the present work are to study the effects of drive cycle properties on the engine behaviour of a hybrid electric vehicle (HEV) and to investigate how this impacts the tailpipe PN emissions and their size distributions (PNSD). Worldwide harmonised light vehicles test cycle (WLTC) testing was conducted, as well as chassis dynamometer emission measurements over a realistic real driving emissions (RDE) speed pattern, using a Euro 5 Toyota Prius HEV with a Cambustion DMS500 sampling PN concentrations at the tailpipe. It is shown that the number of vehicle stops during a test cycle has a direct impact on the re-ignition activity for the HEV. 64 ± 3% of the total PN from WLTC testing was produced during engine re-ignition events while only 6 ± 1% was from stabilised engine operation. Similar proportions were observed for the RDE-style test cycle. The majority of engine reignition and destabilised activity, and hence PN emission, was during the low-speed sections of the drive cycles used. The average PNSD across cycle phases was different between cycles, due to the influence of dynamic properties on engine behaviour and hence the PN emission profile. The PNSD at the engine re-ignition and destabilised events had a merged wide peak with a maximum at 60 nm diameter and a shoulder at 12 nm diameter. The HEV had increased emissions of particles smaller than 23 nm under cold start, but similar overall PN emission values, compared to a warm start. The results of this work highlight the importance of controlling HEV PN emissions to limit human exposure to PN in urban environments where the majority of PN emissions occur. The sensitivity of HEV PN emission factors and PNSD to engine behaviour and, in turn, test cycle dynamic properties, is important to note when considering legislative test cycles, particularly with reference to the freedoms afforded by the RDE test cycle. The results also indicate that substantial improvements to air quality could be made by reducing the particle measurement protocol PN cut-off size to 10 nm.

A comparative study of energy management systems under connected driving: Cooperative car-following case

In this work, we propose connected energy management systems for a cooperative hybrid electric vehicle (HEV) platoon. To this end, cooperative driving scenarios are established under different car-following behavior models using connected and automated vehicles technology, leading to a cooperative cruise control system (CACC) that explores the energy-saving potentials of HEVs. As a real-time energy management control, an equivalent consumption minimization strategy (ECMS) is utilized, wherein global energy-saving is achieved to promote environment-friendly mobility. The HEVs cooperatively communicate and exchange state information and control decisions with each other by sixth-generation vehicle-to-everything (6G-V2X) communications. In this study, three different car-following behavior models are used: intelligent driver model (IDM), Gazis–Herman–Rothery (GHR) model, and optimal velocity model (OVM). Adopting cooperative driving of six Toyota Prius HEV platoon scenarios, simulations under New European Driving Cycle (NEDC), Worldwide Harmonized Light Vehicle Test Procedure (WLTP), and Highway Fuel Economy Test (HWFET), as well as human-in-the-loop (HIL) experiments, are carried out via MATLAB/Simulink/dSPACE for cooperative HEV platooning control via different car-following-linked-vehicle scenarios. The CACC-ECMS scheme is assessed for HEV energy management via 6G-V2X broadcasting, and it is found that the proposed strategy exhibits improvements in vehicular driving performance. The IDM-based CACC-ECMS is an energy-efficient strategy for the platoon that saves: (i) 8.29% fuel compared to the GHR-based CACC-ECMS and 10.47% fuel compared to the OVM-based CACC-ECMS under NEDC; (ii) 7.47% fuel compared to the GHR-based CACC-ECMS and 11% fuel compared to the OVM-based CACC-ECMS under WLTP; (iii) 3.62% fuel compared to the GHR-based CACC-ECMS and 4.22% fuel compared to the OVM-based CACC-ECMS under HWFET; and (iv) 11.05% fuel compared to the GHR-based CACC-ECMS and 18.26% fuel compared to the OVM-based CACC-ECMS under HIL.

An Enhanced Linear Active Disturbance Rejection Rotor Position Sensorless Control for Permanent Magnet Synchronous Motors

An enhanced linear active disturbance rejection controller (ELADRC) based rotor position sensorless field-oriented control scheme for the permanent magnet synchronous motor (PMSM) drivers is proposed in this article. The ELADRC consists of two linear extended state observers (LESOs) and a proportional current controller. One LESO is designed to estimate the back electromotive force (EMF), which is treated as the external disturbance. Then, the rotor position and speed are obtained from the estimated back EMF without any phase delay or chattering problem. The other LESO is designed to estimate the internal disturbances, such as the parameter and current regulation quality variations. The estimated total disturbance is used as a feedforward compensation term in the current control loop to improve the current regulation quality of the plant, which further improves the rotor position estimation performance. The plant combined with the two LESOs is equivalent to an integrator with a unity gain, which is controlled by a simple proportional current controller to generate the desired voltage vector for the pulsewidth modulation operation. Finally, the stability of the closed-loop PMSM drive system with the ELADRC-based scheme is analyzed. Based on the analysis, the parameters of the ELADRC are designed. The proposed scheme is validated by the experimental results for a 275-W salient-pole PMSM drive in which the PMSM is similar to the traction motor used in Toyota Prius hybrid electric vehicles at a reduced scale.

Magnetic Field Analysis of Multi-Flux-Barrier Interior Permanent-Magnet Motors Through Conformal Mapping

An extended analytical method for predicting the open-circuit air-gap field distribution in interior permanent magnet (IPM) machines equipped with multilayer Permanent Magnets (PMs) is proposed in this paper. This presented method is based on the conformal mapping technique. The mapping is used to calculate the relative permeances, which consider the effect of stator slots and rotor saliency on the magnetic field distribution. The open-circuit air-gap field distribution in a multi-flux-barrier IPM can be predicted through the superposition principle. The analytical solution is implemented on: an eight-pole, 50 kW IPM motor used in 2004 Toyota Prius hybrid electric vehicle and four IPMs with two, three, four, and five flux barriers per pole. To verify this extended method, the results are compared with those obtained from the finite-element analysis.

Reducing the variability of hybrid electric vehicle fuel economy in the real world

Apart from improving the fuel economy, a reduction in the variability of the fuel economy is also of significant importance for hybrid electric vehicles. Previously, research on how to optimise the sizes of the powertrain components of hybrid electric vehicles has generally focused on improving the fuel economy over a given driving pattern. The variability of the fuel economy over a realistic range of driving patterns has generally been overlooked, and this can mean that the fuel economy benefits of hybrid electric vehicles are not consistently realised in real-world usage. In a recent study, a new methodology for design optimisation of the powertrain components of hybrid electric vehicles was proposed for the reduction in the variability of the fuel economy due to variation in the driving patterns, but the methodology needs to be validated in real-world usage for practical applicability. In this paper, the methodology is validated in real-world driving conditions. This paper investigated the methodology for 10 real-world driving patterns generated by 10 different drivers over a predefined route consisting of urban and highway driving. The study was carried out using a simulation model of a Toyota Prius hybrid electric vehicle which was considered as the benchmark vehicle. The design produced by the methodology reduced the variability of the fuel economy by 5.3% without reducing the average fuel economy compared with the Toyota Prius over the 10 real-world driving patterns. This demonstrates that the methodology described is applicable to real-world usage.

On–road measurement of gaseous emissions and fuel consumption for two hybrid electric vehicles in Macao

Hybrid electric vehicles (HEVs) are promoted in China to ease increasing pressures of urban air pollution and oil security. In this paper, we measured two Toyota Prius HEVs by using a portable emission measurement system (PEMS) to evaluate their real–world performance with regard to gaseous emission factors and fuel consumption. Our results indicated that their average exhaust emission factors of CO, THC, NOX and CO2 were 0.25±0.08 gkm–1, 0.015±0.002 gkm–1, 0.009±0.005 gkm–1 and 136±21 gkm–1 (i.e., 5.81±0.90 L 100km–1 for fuel consumption) respectively, while driving the averaged on–road traffic pattern. Compared to conventional gasoline and diesel vehicles, the tested HEVs demonstrated significant advantages in simultaneously mitigating major air pollutants (e.g., NOX), greenhouse gas emissions (CO2) and fuel consumption. For example, average CO2 emission factors are reduced by approximately 35% and 15% relative to conventional gasoline and diesel cars in Macao. Unlike conventional gasoline and diesel cars, relative CO2 emission factors of HEVs were much less sensitive to speed change, while their relative NOX emission factors were reduced as average speed became lower. This indicates significant environmental and energy benefits from HEVs under congested driving conditions. Our assessment suggests that HEVs are a competitive technology option for the taxi fleet in Macao with strong advantages in saving fuel cost for taxi drivers and mitigating NOX emissions.

Thermal impact on the control and the efficiency of the 2010 Toyota Prius hybrid electric vehicle

Since introduction of the Prius to the Japanese automotive market in 1997, Toyota has sold more than 1 million of these hybrid electric vehicles in the USA and 3 million in the worldwide market up to 2013. The market penetration of the vehicle has been successful because it provides outstanding fuel economy. However, the reduction in the vehicle’s efficiency under severe weather conditions, especially when the weather is very cold, has not been carefully investigated. The engine’s fuel efficiency decreases when the engine is cooled during use in the electric drive mode, or the battery’s efficiency is also degraded under cold weather conditions. Whereas the impacts of the thermal conditions on the fuel economies of vehicles are being increasingly emphasized, an analysis of these impacts has not been conducted widely because this type of analysis needs to be based on test results obtained from a well-designed environmental chamber that can simulate different thermal conditions. The Advanced Powertrain Research Facility at Argonne National Laboratory has equipped its environmental thermal chamber appropriately and has tested the 2010 Toyota Prius at different ambient room temperatures (−7 ºC, 22 ºC, and 35 ºC). On the basis of the test results, the findings include the fact that the control behavior changes significantly according to the thermal conditions. For instance, the controller forces the engine to be turned on if the engine coolant temperature is below 53 ºC. In addition to the thermal impacts on the controller, performance degradation of the powertrain components and the fuel efficiency levels of the vehicle are also analyzed using the test results. Although this study does not advance a novel idea, the information provided herein should be very useful to researchers seeking to understand controller behavior in the real world under different thermal conditions.

Energy Management in Series-Parallel Hybrid Electric Vehicles Using Fuzzy Logic Controller

This paper describes and introduces a nonlinear model for series-parallel Toyota Prius hybrid electric vehicle (HEV). Required information of driving cycle has been extracted with using Advisor simulation software. Due to optimum power split, we proposed a fuzzy logic compensator that has the duty to split power between energy sources. This compensator help set of planetary gears in order to achieve that goal in accordance to instantaneous power changing. The simulation results of the control strategy, it turns out that our proposed approach raises the efficiency of costs.

State Estimator Design for Series-Parallel Hybrid Electric Vehicles

This paper describes and introduces a nonlinear model for series-parallel Toyota Prius hybrid electric vehicle (HEV). Required information of driving cycle has been extracted with using Advisor simulation software. A proper buoyancy system modeling is essential in order to obtain accurate information of HEV for designing. Due to the great effect of HEVs on environmental pollution, a correct perception of changing in states is necessary. We propose method, based on extended kalman filter (EKF) that is able to overcome problems such as nonlinearity, noise and offset.

Evaluation of the constant volume sampler on plug-in hybrid electric vehicle cold start emission testing

Previous study shows that the constant volume sampler incorrectly measures some of the exhaust gas when testing a plug-in hybrid electric vehicle in the cold start condition when comparing the CO2 results from constant volume sampler and fuel flow meter. The main reason is likely associated with the exhaust left in the vehicle tailpipe and constant volume sampler sampling line. Other factors, such as fuel line expansion and water condensation in the exhaust system, are also considered to have contributions. This article evaluates these issues quantitatively by testing a Toyota Prius hybrid electric vehicle on the industry standard constant volume sampler system combined with both a fuel flow meter measurement and an electronic control unit record for fuel consumption. Cold start test cycles and test cycles with a system pre-purge event show that the constant volume sampler has a significant delay in measuring the exhaust, and the estimated exhaust losses for the test car are 15 g CO2. Tests with a purge event at the end of the driving cycle show that there are approximately 7 g of CO2 trapped in the exhaust system and the constant volume sampler sampling line, and the possible reasons for the discrepancy of the above two points (15 and 7 g) are evaluated. The expansion and air bubble influence the fuel flow meter, and the impact of water condensation on CO2 and CO appears to be negligible.

A Fuzzy Logic Global Power Management Strategy for Hybrid Electric Vehicles Based on a Permanent Magnet Electric Variable Transmission

The major contribution of this paper is to propose a Fuzzy Logic Global Power Management Strategy for Hybrid Electric Vehicles (HEVs) that are driven by the PM-EVT (PM machine—Electric Variable Transmission) powertrain, such that the PM-EVT will have superior advantages over other types of powertrains, including the current Toyota Prius powertrain for series-parallel HEVs. This has been investigated throughout three aspects. The first is the optimum power splitting between the Internal Combustion Engine (ICE) and the PM-EVT. The second is maximizing the vehicle’s energy capture during the braking process. Finally, sustaining the State of Charge (SOC) of the battery is adopted by a robust ON/OFF controller of the ICE. These goals have been accomplished by developing three fuzzy logic (FL) controllers. The FL controllers are designed based on the state of charge of the battery, vehicle’s velocity, traction torque, and the vehicle’s requested power. The integration of the studied system is accomplished via the Energetic Macroscopic Representation (EMR) simulation model strategy based on the software Matlab/Simulink. The PM-EVT based HEV system with the proposed power management strategy is validated by comparing to the Toyota Prius HEV. The vehicle’s performances have been analyzed throughout a combined long-trip driving cycle that represents the normal and the worst operating conditions. The simulation results show that global control system is effective to control the engine’s operating points within the highest efficiency region, exploiting of EVT machines for capturing maximum braking energy, as well as to sustain the SOC of the battery while satisfy the drive ability. The proposed control strategy for the studied HEVs sounds interesting and feasible as supported by a large amount of simulation results.

The Conversion of a Hybrid Electric Vehicle into a Plug-in Hybrid Electric Vehicle

Towards low carbon living and clean air quality is CLP Power Hong Kong Ltd. (CLP)'s energy vision and to achieve this goal, the promotion of a cleaner mode of transportation in Hong Kong has been one of CLP's key green initiatives. Recently, CLP has successfully converted a few Toyota Prius hybrid electric vehicles (HEV) into plug-in hybrid electric vehicles (PHEV). Different from the HEV, a PHEV allows the driver to plug into a socket to connect the vehicle to the electrical grid to charge its larger battery pack that replaced the original smaller one. The objective of the conversion exercise is to test the capability and gauge the benefits of the converted PHEV to run on electricity as much as possible, whilst keeping the capability to switch back to conventional combustion engine if required for longer trips. This paper addresses the conversion technical details and shares the operation experience of employing a PHEV in the corporate fleet as well as discusses the underlying business assessment of such exercise. The benefits achieved with the PHEV in terms of reduced emissions and fuel cost savings are also reviewed.

Development of a modal emissions model for a hybrid electric vehicle

With the growing market share of hybrid electric vehicles (HEVs), new methods are needed for estimating their actual energy use and emissions in order to support emission inventories. This research quantifies criteria associated with startup and shutdown of the internal combustion engine (ICE) for a 2001 Toyota Prius HEV and develops a modal tailpipe emissions model under hot stabilized conditions. The engine is found to be “off” below thresholds of engine power demand that are speed and acceleration dependent. Vehicle specific power (VSP) is used as the basis for modeling emissions. The predicted cycle emissions of CO, NO x and HC for individual cycles are subject to large relative errors, but the overall emission predictions for the average of multiple cycles have relative errors within 10% for each selected pollutant. The ICE engine status identification method is recommended for application to model HEV emissions under actual driving conditions.

Impact of SiC Devices on Hybrid Electric and Plug-In Hybrid Electric Vehicles

The application of silicon carbide (SiC) devices as battery interface, motor controller, etc., in a hybrid electric vehicle (HEV) will be beneficial due to their high-temperature capability, high-power density, and high efficiency. Moreover, the light weight and small volume will affect the whole powertrain system in a HEV and, thus, the performance and cost. In this paper, the performance of HEVs is analyzed using the vehicle simulation software Powertrain System Analysis Toolkit (PSAT). Power loss models of a SiC inverter based on the test results of latest SiC devices are incorporated into PSAT powertrain models in order to study the impact of SiC devices on HEVs from a system standpoint and give a direct correlation between the inverter efficiency and weight and the vehicle's fuel economy. Two types of HEVs are considered. One is the 2004 Toyota Prius HEV, and the other is a plug-in HEV (PHEV), whose powertrain architecture is the same as that of the 2004 Toyota Prius HEV. The vehicle-level benefits from the introduction of SiC devices are demonstrated by simulations. Not only the power loss in the motor controller but also those in other components in the vehicle powertrain are reduced. As a result, the system efficiency is improved, and vehicles that incorporate SiC power electronics are predicted to consume less energy and have lower emissions and improved system compactness with a simplified thermal management system. For the PHEV, the benefits are even more distinct; in particular, the size of the battery bank can be reduced for optimum design.

Toyota Prius HEV neurocontrol and diagnostics

A neural network controller for improved fuel efficiency of the Toyota Prius hybrid electric vehicle is proposed. A new method to detect and mitigate a battery fault is also presented. The approach is based on recurrent neural networks and includes the extended Kalman filter. The proposed approach is quite general and applicable to other control systems.

Comprehensive drive train efficiency analysis of hybrid electric and fuel cell vehicles based on motor-controller efficiency modeling

From the point of view of overall hybrid electric vehicle (HEV) and fuel cell vehicle (FCV) drive train efficiency, the research focus is mainly on the efficiency analysis of the power train components, which prove to be an integral part of modern HEV and FCV drive trains. The critical portion of any HEV electrical system consists of a power electronic converter (inverter) and a suitable traction motor. Thus, the efficiency analysis of the inverter/motor is of prime importance for the calculation of the overall efficiency of the drive trains. This paper aims at modeling the efficiencies of the traction motor/controller through efficiency maps. Efficiency maps are a convenient way to represent motor drive systems of large and complex systems, like that of a HEV. The paper uses the advanced vehicle simulator (ADVISOR) software for the simulations of a large-sized car, similar to a Chevy Lumina, over the urban dynamometer-driving schedule and highway fuel economy test drive cycles. Furthermore, the paper investigates the traction motor efficiency maps and consequent overall drive train efficiencies of commercially available Honda Insight and Toyota Prius HEVs. In all the case studies, the aim is to analyze the overall drive train efficiency over the city and highway drive cycles based on the inverter/motor efficiency maps.