Hybrid vehicle power management modeling and refinement

The power management strategy in many hybrid vehicles is based on expert rules and thresholds. These rule-based strategies can result in good efficiency in term of fuel economy and emissions if their thresholds and rules are accurate. However, due to the complexity and the non-linearity of the hybrid powertrain, determining accurate thresholds and rules is neither explicit nor straightforward, and experts in most cases fail to define these thresholds and rules with enough accuracy. Based on this fact, the objective of this paper is to propose a method to improve this rule-based strategy by refining its thresholds and rules. To achieve this, we used an optimization method (dynamic programming) to calculate the optimal power management, determine the optimal control signals, and extract efficient thresholds and rules that can be used in real time. Finally, simulation results for the three strategies (optimal, simple and refined strategy) are shown and discussed.     

Development of a fail-safe control strategy based on evaluation scenarios for an FCEV electronic brake system

This study presents a few fail-safe control strategies based on reliability evaluation scenarios for the electronic brake systems of green cars in several critical cases. CarSim and MATLAB Simulink were used to develop the FCEV model with regenerative braking involving EWBs and EMBs. The proposed reliability evaluation scenarios were simulated, and a few fail-safe control algorithms were verified using the proposed reliability evaluation scenarios with the developed FCEV simulation model. The reliability evaluation scenarios were developed using a combination of driving modes and FMEA results for these electronic brake systems.     

Design methodology to reduce the chest deflection in US NCAP and EURO NCAP tests

There have not been many studies on the factors that affect chest deflection, although the US NCAP thoracic injury criterion was recently shifted from the 3-msec clip to chest deflection. This study explored these factors and proposed a design methodology for the factors to minimize chest deflection. Because injuries can become severe if the driver crashes against the vehicle interior, this study also sought a solution using a penalty function to prevent crashes with the interior and minimize injuries. First, a MADYMO model was made to simulate US NCAP and EURO NCAP tests by one-to-one and stochastic verifications. Second, a sensitivity analysis was conducted to find the major factors that affect chest deflection. Lastly, the factors identified via the sensitivity analysis were optimized to propose design guidelines that helped vehicles receive high star ratings in US NCAP and EURO NCAP tests and helped minimize the possibility of hard contact between the driver and the vehicle interior by utilizing a penalty function and the Taguchi method.     

Development of a control strategy based on the transmission efficiency with mechanical loss for a dual mode power split-type hybrid electric vehicle

In this study, a control strategy for a dual mode power split-type hybrid electric vehicle (HEV) is developed based on the powertrain efficiency. To evaluate the transmission characteristics of the dual mode power split transmission (PST), a mechanical loss model of the transmission (TM loss) is constructed. The transmission efficiency, including the TM loss, is evaluated for the dual mode PST. Two control strategies for the dual mode PST are proposed. An optimal operation line (OOL) control strategy is developed to maintain a high engine thermal efficiency by controlling the engine operation point on the OOL. A speed ratio (SR) control strategy is proposed to obtain a greater transmission efficiency by shifting the engine operation point when the dual mode PST operates near the mechanical points. Using the TM loss and the proposed control strategies, a vehicle performance simulation is conducted to evaluate the performance of the two control strategies for dual mode PST. The simulation results demonstrate that, for the SR control strategy, the engine efficiency decreases because the engine operates beyond the OOL. However, the transmission efficiency of the dual mode PST increases because the PST operates near the mechanical point where the PST shows the greatest transmission efficiency. Consequently, the fuel economy of the SR control strategy is improved by 3.8% compared with the OOL control strategy.     

Optimization of intake port design for SI engine

It is well known that in-cylinder flow is very important factor for the performance of SI engine. An appropriate in-cylinder flow pattern can enhance the turbulence intensity at spark time, therefore increasing the stability of combustion, reducing emission and improving fuel economy. In this paper, the effect of intake port design on in-cylinder flow is studied. It is found a vortex existed at the upper side of intake port of a production SI engine used in the study, during the intake stroke, which will reduce both tumble ratio and volumetric efficiency. A minor modification on intake port is made to eliminate the vortex and increase tumble ratio while keeping volumetric efficiency at the same level. It is demonstrated that the increase in tumble in the new design results in a 20 per cent increase in the fuel vaporization. In this study, both KIVA and STAR-CD are used to simulate the engine cold flow, as well as ICEM CFD and es-ice used as pre-processor respectively due to the complexity of engine geometry. Simulation results from KIVA and STAR-CD are compared and analyzed.     

Robust design optimization of suspension system by using target cascading method

This study presents the robust design optimization process of suspension system for improving vehicle dynamic performance (ride comfort, handling stability). The proposed design method is so called target cascading method where the design target of the system is cascaded from a vehicle level to a suspension system level. To formalize the proposed method in the view of design process, the design problem structure of suspension system is defined as a (hierarchical) multilevel design optimization, and the design problem for each level is solved using the robust design optimization technique based on a meta-model. Then, In order to verify the proposed design concept, it designed suspension system. For the vehicle level, 44 random variables with 3% of coefficient of variance (COV) were selected and the proposed design process solved the problem by using only 88 exact analyses that included 49 analyses for the initial meta-model and 39 analyses for SAO. For the suspension level, 54 random variables with 10% of COV were selected and the optimal designs solved the problem by using only 168 exact analyses for the front suspension system. Furthermore, 73 random variables with 10% of COV were selected and optimal designs solved the problem by using only 252 exact analyses for the rear suspension system. In order to compare the vehicle dynamic performance between the optimal design model and the initial design model, the ride comfort and the handling stability was analyzed and found to be improved by 16% and by 37%, respectively. This result proves that the suggested design method of suspension system is effective and systematic.     

Integration of a single cylinder engine model and a boost system model for efficient numerical mapping of engine performance and fuel consumption

A numerical engine mapping methodology is proposed for the engine performance and fuel consumption map generation. An integrated model is developed by coupling a single cylinder GT-Power® engine model with a MATLAB/ Simulink® based boost system model to simulate a turbocharged diesel engine over the entire engine operating speed and load ranges within reasonable computational constraints. A single cylinder engine model with the built-in multi-zone combustion modeling option in GT-Power® is configured as a predictive engine model. The cycle averaged simulation result from the engine model is used as the boundary conditions of the boost system including intake and exhaust manifolds and a turbocharger. The boost system model developed in MATLAB/Simulink® platform calculates the intake and exhaust conditions which are fed back to the engine model. The integrated system model predicts the performance and fuel consumption of a turbocharged diesel engine with better predictive capability than mean value engine models. Its computational time is fast enough to simulate the engine over the entire engine operation range compared to multi-cylinder engine models.     

Fuzzy energy management strategy for a hybrid electric vehicle based on driving cycle recognition

By considering the effect of the driving cycle on the energy management strategy (EMS), a fuzzy EMS based on driving cycle recognition is proposed to improve the fuel economy of a parallel hybrid electric vehicle. The EMS is composed of driving cycle recognition and a fuzzy torque distribution controller. The current driving cycle is recognized by learning vector quantization in driving cycle recognition. The torque of the engine and the motor is controlled by a fuzzy torque distribution controller based on the required torque of the hybrid powertrain and the battery state of charge. The membership functions and rules of the fuzzy torque distribution controller are optimized simultaneously by using particle swarm optimization. Based on the identification results of driving cycle recognition, the fuzzy torque distribution controller selects the corresponding membership function and rule to control the hybrid powertrain. The simulation research based on ADVISOR demonstrates that this EMS improves fuel economy more effectively than fuzzy EMS without driving cycle recognition.     

RFID技术在广东省多义性标识试点方案中的应用分析

随着广东省高速公路网复杂度加大,路径识别将成为联网收费精确拆分必须解决的关键问题。经过对各种路径标识技术的比较,选用RFID技术在粤东区域进行路径识别试点。通过试点项目初步认证了RFID技术的可行性和稳定性,同时也为该技术在广东省高速公路联网收费中推广应用打下基础。     

Real-time characterisation of driver steering behaviour

In recent years the application of driver steering models has extended from the off-line simulation environment to autonomous vehicles research and the support of driver assistance systems. For these new environments there is a need for the model to be adaptive in real time, so the supporting vehicle systems can react to changes in the driver, their driving style, mood and skill. This paper provides a novel means to meet these needs by combining a simple driver model with a single-track vehicle handling model in a parameter estimating filter – in this case, an unscented Kalman filter. Although the steering model is simple, a motion simulator study shows it is capable of characterising a range of driving styles and may also indicate the level of skill of the driver. The resulting filter is also efficient – comfortably operating faster than real time – and it requires only steer and speed measurements from the vehicle in addition to the reference path. Adaptation of the steer model parameters is demonstrated along with robustness of the filter to errors in initial conditions, using data from five test drivers in vehicle tests carried out on the open road.

Abbreviations: ADAS: advanced driver assistance systems; CG: centre of gravity; CAN: controller area network; EKF: extended Kalman filter; GPS: global positioning system; UKF: unscented Kalman filter