Implementation of discharging/charging current sensorless state-of-charge estimator reflecting cell-to-cell variations in lithium-ion series battery packs

This paper offers novel insights to the design and implementation of an innovative state-of-charge (SOC) estimator for the lithium-ion (Li-Ion) series battery pack. The most interesting feature of this approach is that it can utilize information from each filtered terminal voltage of the Li-Ion cells connected in series for SOC estimation of the battery pack. Without actual sensing each discharging/charging current (DCC) applied to the Li-Ion cells, it is possible to extract each DCC estimation from the corresponding filtered terminal voltages with an equivalent electrical circuit model (EECM) identification of all Li-Ion cells in the battery pack. There are two advantages to SOC estimation of the battery pack with this approach. First, the proposal can be implemented simply and effectively, reducing the computational steps required for SOC estimation. By reducing computational steps, the proposal is expected to be more cost-effective. Second, the approach guarantees an improved SOC performance, even if the battery pack results in inevitable cell-to-cell variation among Li-Ion cells. Accordingly, there are fewer differences to previously estimated DCCs among Li-Ion cells. Specifically, all values from the estimated DCCs are properly compensated for by simultaneous parameter modification according to each cell’s electrochemical characteristics. Experimental results clearly demonstrate that our DCC sensorless SOC estimator provides robust SOC performance for the battery pack. This approach considered an experimental battery pack (12S1P) connected in series using 2.6 Ah LiCoO2 cells produced by Samsung SDI.     

Quasi steady-state aerodynamic model development for race vehicle simulations

Presented in this paper is a procedure to develop a high fidelity quasi steady-state aerodynamic model for use in race car vehicle dynamic simulations. Developed to fit quasi steady-state wind tunnel data, the aerodynamic model is regressed against three independent variables: front ground clearance, rear ride height, and yaw angle. An initial dual range model is presented and then further refined to reduce the model complexity while maintaining a high level of predictive accuracy. The model complexity reduction decreases the required amount of wind tunnel data thereby reducing wind tunnel testing time and cost. The quasi steady-state aerodynamic model for the pitch moment degree of freedom is systematically developed in this paper. This same procedure can be extended to the other five aerodynamic degrees of freedom to develop a complete six degree of freedom quasi steady-state aerodynamic model for any vehicle.     

Driver steering and muscle activity during a lane-change manoeuvre

The article reports an experimental study of driver steering control behaviour in a lane-change manoeuvre. Eight test subjects were instrumented with electromyography to measure muscle activation and co-contraction. Each subject completed 30 lane-change manoeuvres with one vehicle on a fixed-base driving simulator. For each driver, the steering torque feedback characteristic was changed after every ten manoeuvres; the response of the vehicle to steering angle inputs was not changed. Drivers' control strategies were found to be robust to changes in steering torque feedback. Path-following errors, muscle activity and muscle co-contraction all reduce with the number of lane-changes performed by the driver, suggesting the existence of a learning process. Comparing the test subjects, there was some evidence that high levels of co-contraction were used to allow high-frequency steering inputs to be generated. The results contribute to the understanding of vehicle-driver (and more generally, human-machine) dynamic interaction.     

Analysis of the shifting behavior of a novel clutchless geared smart transmission

Conventional geared transmissions use some kinds of clutches to control the power flow from an internal combustion engine to the driveline while shifting gears. However, the shifting performance is seriously affected by the clutch engagement and an unavoidable drop in the torque may occur when the clutch is disconnected. Moreover, wear of the clutch, the need for hydraulic equipment, and the load limit may together aggravate the limits of the clutch system. For this reason, as a novel transmission without a clutch, the clutchless geared smart transmission (henceforth CGST) is proposed by our research team. The CGST controls the power flow in a multiple-input gear-train by controlling the electric motor attached to the planetary gear system. However, no CGST has been realized in an actual vehicle thus far, and the performance has been predicted only theoretically. In this research, we analyzed the achievable performance based on a developed CGST dynamic model with a typical CGST structure. In addition, a CGST gear-shifting algorithm is proposed for use with the dynamic model. From the simulation results, the CGST does not show an abrupt drop in its torque or oscillation while shifting gears due to the absence of a discontinuous power flow. The developed dynamic model can serve as a performance reference for the CGST. Moreover, it can be used as a simulation tool for developing a gear-shifting control logic scheme.     

Impact of hilly road information on fuel economy of FCHEV based on parameterization of hilly roads

Under real-life driving conditions, hilly roads are prevalent. Hilly road profile substantially influences fuel economy (FE) due to large impacts (increase or decrease) on power demand profile. Thus, the utilization of future altitude profile information has large potential to improve FE. In this paper, for optimal energy management of fuel cell hybrid electric vehicles (FCHEV), we investigate how much FE could potentially be improved when future altitude profile information is available. In particular, the simulation results are analyzed to justify the reason for this potential improvement and to identify which characteristics of hilly roads leads to large FE improvements. First of all, four statistical parameters are defined to characterize hilly roads: mean value, standard deviation (STD), distance interval (DI), and total distance. Then, several types of virtual hilly roads are generated based on various parameter combinations. In order to evaluate the potential FE improvement two energy management strategies (EMSs) are utilized: the first is Dynamic Programming, which evaluates the globally optimal FE when future hilly road information is available; the other is the Equivalent Consumption Minimization Strategy (ECMS) with adaptive equivalent factor for charge-sustenance, which represents the baseline EMS when future hilly road information is not available. The results show that downhill roads have much larger potential than uphill roads do for FE improvements when the future altitude profile is properly used for EMS. Furthermore, if the battery capacity is not large enough to handle the difference in potential energy, future hilly road information is more important to prevent violations of the maximum state-of-charge bound.     

Fatigue life prediction of a rubber material based on dynamic crack growth considering shear effect

This paper suggests a fatigue life calculation method (A fatigue life calculation method is suggested) for rubber components based on the dynamic crack growth considering shear effect. Dynamic tearing tests were carried out, and the crack length was measured using an optical microscope to calculate the dynamic crack growth rate which characterizes and determines the fatigue life. The algorithm was numerically implemented in finite element code, ABAQUS standard, by using the user subroutine and applied to several rubber components. In the finite element analysis, deformation mode of an element was classified into tension and shear, and a weighting factor was multiplied to a strain energy density according to the degree of shear strain. Tension and compression of an elliptic dumbbell specimen was simulated in order to verify the material parameters of the suggested fatigue life prediction equation and to enhance the reliability of the algorithm. Finally, the fatigue life of a vehicle suspension bushing was calculated and compared with test. There were good agreements in the failure location and the magnitude of the fatigue life.     

Approach to functional safety-compliant ECU design for electro-mechanical brake systems

In this paper, we propose a design approach to a functional safety-compliant ECU for an electro-mechanical brake (EMB) control system or an electronic wedge brake (EWB) control system. Brake actuators in a brake-by-wire (BBW) system such as EMB or EWB are characterized by the safety-critical functions which are now executed by using many electric and electronic devices with application software. Based on hazard analysis and risk assessments of the automotive functional safety standard ISO 26262, the proposed EMB control system should be ASIL-D-compliant, which is the highest ASIL level. To this end, a hardware and a software design method is introduced to implement functionl safety-oriented monitoring functions which are based on an asymmetric dual-core architecture with an external watchdog processor. It is shown by using EMB hardware-In-the-Loop-Simulation (HILS) that the proposed ECU design approach is very effective when a hardware fault or software execution faults occur in the EMB ECU, moreover, this functional safety-compliant design can be well combiled with the sensor fault-tolerant control logic.     

In-vehicle technology for self-driving cars: Advantages and challenges for aging drivers

The development of self-driving cars or autonomous vehicles has progressed at an unanticipated pace. Ironically, the driver or the driver-vehicle interaction is a largely neglected factor in the development of enabling technologies for autonomous vehicles. Therefore, this paper discusses the advantages and challenges faced by aging drivers with reference to in-vehicle technology for self-driving cars, on the basis of findings of recent studies. We summarize age-related characteristics of sensory, motor, and cognitive functions on the basis of extensive age-related research, which can provide a familiar to better aging drivers. Furthermore, we discuss some key aspects that need to be considered, such as familar to learnability, acceptance, and net effectiveness of new in-vehicle technology, as addressed in relevant studies. In addition, we present research-based examples on aging drivers and advanced technology, including a holistic approach that is being developed by MIT AgeLab, advanced navigation systems, and health monitoring systems. This paper anticipates many questions that may arise owing to the interaction of autonomous technologies with an older driver population. We expect the results of our study to be a foundation for further developments toward the consideration of needs of aging drivers while designing self-driving vehicles.     

Methodology for bus structure torsion stiffness and natural vibration frequency prediction based on a dimensional analysis approach

Engineering bus design requires testing of bus structures prototypes in order to guarantee a certain level of strength and an appropriate static and dynamic behavior of the bus superstructure when exposed to road loads. However, experimental testing of real bus structures is very expensive as it requires expensive resources and space. If testing is done on a scale bus model the previous required expenses are considerably reduced. Therefore, a novel methodology based on dimensional analysis applied to bus structure prediction to evaluate the bus structure static and dynamic performance is proposed. The static performance is evaluated attending to torsion stiffness and the dynamic in terms of the natural vibration frequencies and rollover threshold. A scale bus has been manufactured and dimensionless parameters have been defined in order to project the results obtained in the scale bus model to a larger model. Validation of the proposed methodology has been carried out under experimental and finite element analysis.     

Durability prediction for automobile aluminum front subframe using nonlinear models in virtual test simulations

This research work presents fatigue life evaluation techniques for an automotive vehicle aluminum front subframe using virtual test simulation technology with nonlinear suspension components model. The technology was used for improving the accuracy of the polynomial model used in conventional analysis. The proposed nonlinear suspension components models were developed using direct approach. The effects of the nonlinear elements on the prediction of the fatigue life were also analyzed. Actual aluminum front subframe was tested using half-car road test simulator to verify the accuracy of the models. It was found that the proposed nonlinear models yield more accurate results than conventional polynomial models. The proposed virtual test simulation technology with nonlinear suspension components model can be used to predict fatigue life for vehicle chassis structures more accurately.