Search Results

Operating condition of rotor embedded magnet materials for permanent magnet synchronous motor (PMSM) critically affect electric vehicle (EV) range and dynamic characteristics. The rotor liquid cooling technique has a deep influence on PMSM performance improvement, and begin to be studied and applied increasingly in EV field. Here, the fluid, thermal, and electromagnetic characteristics of motor with and without hollow-shaft cooling are researched comprehensively based on 100 kW PMSM with housing water jacket (HWJ) and hollow-shaft rotor water jacket (SWJ). The solid models are constructed considering temperature-dependent power loss and anisotropic thermal conductivity. After the fluid models are set up by using Reynolds stress model (RSM), conjugate heat transfer is conducted through computational fluid dynamics (CFD) simulation, and is verified by real PMSM test bench experiments.

To reduce the energy consumption level of electric vehicles, the working range of the regenerative braking system will gradually expand to the high state of charge of the battery. The time delay in the control signal transmission path of the high state of charge regenerative braking control process will affect the regenerative braking. At the same time, regenerative braking under a high state of charge puts forward higher requirements for the control accuracy of regenerative current. In the research of this paper, the motor model, battery model, and vehicle dynamics model are firstly established by using MATLAB/Simulink, and the dynamic relationship between regenerative current and regenerative braking torque is analyzed at the same time. Considering the system time delay, this paper proposes a high-charge regenerative braking control strategy (SPPC) that combines Smith prediction and prescribed performance control.

The electric vehicles and the intelligent vehicles put forward to new requirements for the brake system, such as the vacuum-independent braking, automatic or active braking, and regenerative braking, which are the key link for the vehicle’s safety and economy. However, the traditional vacuum brake booster is no longer able to meet these requirements. In this article, a novel integrated power-assisted actuator of brake system is proposed to satisfy the brake system requirements of the electric vehicles and intelligent vehicles. The electronic brake booster system is designed to achieve the function of boosting pedal force of driver, being independent on vacuum source, supplying autonomous or active braking. It is mainly composed of a permanent magnet synchronous motor (PMSM), a two-stage reduction transmission (gears and a ball screw), a servo body, and a reaction disk. The scheme design and power-assisted braking control are the key for the electronic actuator.

The vehicle driveline suffers low frequency torsional vibration due to the abrupt change of input torque and torque fluctuation under variable frequency. This problem can be solved by model based control, so building a control oriented driveline model is extremely important. In this paper, an on-line recursive identification method is proposed for control oriented model and validated based on an electric car. First of all, the control oriented driveline model is simplified into a six-parameter model with double inertia. Secondly, based on stability analysis, motor torque and motor speed are chosen as input signal for on-line model identification. A recursive identification algorithm is designed and implemented based on Simulink. Meanwhile a detail model of the vehicle which considering driveline parameter variation is built based on ADAMS. Thirdly, on-line identification is conducted by using co-simulation of ADAMS and Simulink.

In this paper, a novel driver model is proposed to track vehicle speed in MIL (Model-in-the-Loop) test system, which has structural consistency with HIL (Hardware-in-the-Loop) test system. First, the MIL test system which contains models of driver, vehicle and test bench is established. Second, according to the connections of the established models in Matlab/Simulink environment, the vehicle speed is calculated in vehicle model. Emphatically, through the deviation between driving cycle speed and calculated vehicle speed, PI controller in driver model adjusts the vehicle speed to ideal point through sending the torque command to drive motor, the ILC (Iterative Learning Control) controller modifies and stores P value of PI controller. Then, in order to obtain the better modification of PI controller, iterative learning control algorithm is deeply researched in term of types and parameters.

Wiper noise generated in the wiping process is one of the main influence factors affecting the driving comfort. Since the dynamic contact pressure of the contact between a blade and a windshield glass is difficult to be measured, it is also difficult to predict the degree of the wiper noise. In this paper, in the view of the reversal noise problem of a passenger-vehicle windscreen wiper system, the system dynamic models of the both wipers on the sides of the driver and copilot were built as considering the blade deformation and the elastic contact between the blades and the windscreen glass, including the crank pivot, the four linkage mechanism, the wiper blades, the wiper arms and the windscreen glass. The motion of the wiper system and the pressure distributions between the blades and the windscreen glass were analyzed under the half-dry condition.

This study proposes a method for presenting maneuver request information of accelerator pedal to a driver via the accelerator pedal itself. By applying periodic force like vibration on an accelerator pedal, information is transferred to the driver without displacing the accelerator pedal. In this study, the authors focus on a saw-tooth wave as the periodic force. When the saw-tooth-waved force is applied on the accelerator pedal, a human driver feels as if the accelerator pedal is knocked by someone periodically. In addition, information about the quantity of requested maneuver can be transferred by the amplitude of the saw-tooth wave. Based on these facts, the saw-tooth wave is modified and optimized empirically with ten human drivers so that the information of direction is transferred most reliably. In addition, the relationship between the amplitude of the saw-tooth wave and requested quantity of the pedal maneuver that the drivers feel is formulated.

Controllability (C) is the parameter that determines the Automotive Safety Integrity Level (ASIL) of each hazardous event based on an international standard of electrical and/or electronic systems within road vehicles (ISO 26262). C is classified qualitatively in ISO 26262. However, no specific method for classifying C is described. It is useful for C classification to define a specific classification based on objective data. This study assumed that C was classified using the percentage of drivers who could reduce Severity (S) in one or more classes compared with the S class in which the driver did not react to a hazardous event. An experiment simulated a situation with increased risk of collision with a leading vehicle due to insufficient brake force because of brake-assist failure when the experiment vehicle decelerated from 50 km/h on a straight road.

Electric vehicles have become more popular and may be involved in fires due to accidents. However, characteristics of fires in electric vehicles are not yet fully understood. The electrolytic solution of lithium-battery vehicles is inflammable, so combustion characteristics and gases generated may differ from those of gasoline cars. Therefore, we conducted fire tests on lithium-ion battery vehicles and gasoline vehicles and investigated the differences in combustion characteristics and gases generated. The fire tests revealed some differences in combustion characteristics. For example, in lithium-ion battery vehicles, the battery temperature remained high after combustion of the body. However, there was almost no difference in the maximum CO concentration measured 0.5 to 1 m above the roof and 1 m from the side of the body. Furthermore, HF was not detected in either type of vehicle when measured at the same positions as for CO.

Hybrid, plug-in hybrid, and electric vehicles have enthusiastically embraced rechargeable Li-ion batteries as their primary/supplemental power source of choice. Because the state of charge (SoC) of a battery indicates available remaining energy, the battery management system of these vehicles must estimate the SoC accurately. To estimate the SoC of Li-ion batteries, we derive a normalized state-space model based on Li-ion electrochemistry and apply a Bayesian algorithm. The Bayesian algorithm is obtained by modifying Potter's squareroot filter and named the Potter SoC tracker (PST) in this paper. We test the PST in challenging test cases including high-rate charge/discharge cycles with outlier cell voltage measurements. The simulation results reveal that the PST can estimate the SoC with accuracy above 95% without experiencing divergence.

We present research in progress to develop and implement a transportable instrumentation package (TIP) to collect driver data in a vehicle. The overall objective of the project is to investigate the symbiotic relationship between humans and their vehicles. We first describe the state-of-art technologies to build the components of TIP that meet the criteria of ease of installation, minimal interference with driving, and sufficient signals to monitor driver state and condition. This method is a viable alternative to current practice which is to first develop a fully instrumented test vehicle, often at great expense, and use it to collect data from each participant as he/she drives a prescribed route. Another practice, as for example currently being used in the SHRP-2 naturalistic driving study, is to install the appropriate instrumentation for data collection in each individual's vehicle, often requiring several hours.

In recent years, the residential and transportation sectors have made significant strides in reducing energy consumption, mainly by focusing efforts on low-hanging fruit in each sector independently. This independent viewpoint has been successful in the past because the user needs met and resources consumed in each sector have been clearly distinct. However, the trend towards vehicle electrification has blurred the boundary between the sectors. With both the home and vehicle now relying upon the same energy source, interactions between the systems can no longer be neglected. For example, when tiered utility pricing schemes are considered, the energy consumption of each system affects the cost of the other. In this paper, the authors present an integrated Home-Vehicle Simulation Model (HVSM), allowing the designer to take a holistic view.

In this study, a scheme for controlling the deceleration rate required to alleviate shockwave propagation in a vehicle platoon is proposed. Assuming a three-vehicle platoon, the deceleration rates of the 2nd and the 3rd vehicles were modeled so as to minimize the speed of the shockwave that propagates through the platoon. The effect of the decelerating two vehicles on a 4th following vehicle was also evaluated. Numerical analysis showed that an earlier and slightly more rapid deceleration rate significantly decreased the speed of the shockwave propagated by the first three vehicles. Furthermore, even though the shockwave was amplified through the 2nd to 4th vehicles, this negative effect could be eliminated by applying the same control strategy to the 3rd and 4th vehicles.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

Seat belts for rear passengers are not commonly used, even though they can significantly reduce fatalities. A passenger seat belt reminder (PSBR) is installed in order to encourage seat belt use, but the effectiveness of PSBRs on the rear seat passenger has not yet been proven. We have developed a methodology to assess PSBR effectiveness. There are two pathways to encourage seat belt use. The first is that PSBR directly facilitates the passenger's use. The second is to motivate the driver request passengers to use seat belts. In the experiment, we asked participants sitting in the driver's seat to select one of five ranks of likelihood to encourage the passenger when a PSBR was presented. We also asked participants sitting in the rear passenger seat to select the rank of likelihood to use the belt voluntarily with PSBR and that to use the belt when the driver requested. The degree of likelihood was quantified by averaging the assigned percentage values to the ranks.

This paper is the third in the series of documents designed to record the progress on the SAE Plug-in Electric Vehicle (PEV) communication task force. The initial paper (2010-01-0837) introduced utility communications (J2836/1™ & J2847/1) and how the SAE task force interfaced with other organizations. The second paper (2011-01-0866) focused on the next steps of the utility requirements and added DC charging (J2836/2™ & J2847/2) along with initial effort for Reverse Power Flow (J2836/3™ & J2847/3). This paper continues with the following: 1. Completion of DC charging's 1st step publication of J2836/2™ & J2847/2. 2. Completion of 1st step of communication requirements as it relates to PowerLine Carrier (PLC) captured in J2931/1. This leads to testing of PLC products for Utility and DC charging messages using EPRI's test plan and schedule. 3. Progress for PEV communications interoperability in J2953/1.

It is becoming more and more necessary to achieve a sustainable low-carbon society by mobility not depending on oil. Electric vehicles are appropriate for such a society, but expensive battery cost and long charging time prohibit the promotion of EVs. One of the solutions is minimizing battery usage by ultra-low fuel efficiency, so we developed an ultrahigh-efficient electric commuter concept car “C-ta”, which requires as small a battery as possible. We assumed that drivers would use the car as a second car for short-distance daily use, such as commuting, shopping, transportation of family, etc. In order to improve fuel efficiency, we mainly considered an ultra-light weight body and chassis, to which CFRP (carbon fiber reinforced plastic) greatly contributes, ultra-low rolling resistance tires, and highly accurate vehicle control technology with four in-wheel motors.

Naturalistic driving data has been accumulated by driving data recorders to understand factors that contribute to collisions. Among the rear end conflicts at signalized intersections in the data, conflict data between the following vehicles and suddenly stopping lead vehicles were frequently observed just after their start. To investigate the following drivers' behavior in a realistic driving situation without collision danger, an instrumented vehicle equipped with a liquid-crystal display ahead of the windshield was developed, and an experiment reproducing such conflict on the display was conducted. It was found that a lead vehicle's rapid start (2.8 m/s₂ on average) before quitting its right turn caused the following vehicle's brake reaction time to be longer than a slow start (0.8 m/s₂ on average) did. This result suggests that a following driver's premature decision to start rapidly increases the risk of rear end collisions.

Effects of hands-free phone conversations on drivers' visual behavior and detection performance were examined using a gaze-tracking device and fixed-based driving simulator. The participants engaged in various conversation tasks (simple/arithmetic/unconstrained) while following a lead vehicle. The results indicated that hands-free-phone conversations, even if the contents are not subjectively demanding, can affect a driver's visual behavior. The increment of binocular gaze dissociation induced by conversing on a phone indicates that a driver's attention is diverted from the external scenery to the conversation. Furthermore, this observed dissociation of binocular gaze may represent a resting position, which is revealed only when binocular fusion is disrupted by occluding one eye.

Electric Power-Assisted Steering (EPAS) is a new power steering technology that will define the future of vehicle steering. The assist of EPAS is the function of the steering wheel torque and vehicle velocity. The assist characteristic of EPAS is set by control software, which is one of the key issues of EPAS. The straight-line type assist characteristic has been used in some current EPAS products, but its influence on the steering maneuverability and road feel hasn't been explicitly studied in theory. In this paper, the straight-line type assist characteristic is analyzed theoretically. Then a whole vehicle dynamic model used to study the straight-line type assist characteristic is built with ADAMS/Car and validated with DCF (Driver Control Files) mode of ADAMS/Car. Based on the whole vehicle dynamic model, the straight-line type assist characteristic's influence on the steering maneuverability and road feel is investigated.