Cooperative regenerative braking control for front-wheel-drive hybrid electric vehicle based on adaptive regenerative brake torque optimization using under-steer index

In this study, cooperative regenerative braking control of front-wheel-drive hybrid electric vehicle is proposed to recover optimal braking energy while guaranteeing the vehicle lateral stability. In front-wheel-drive hybrid electric vehicle, excessive regenerative braking for recuperation of the maximum braking energy can cause under-steer problem. This is due to the fact that the resultant lateral force on front tire saturates and starts to decrease. Therefore, cost function with constraints is newly defined to determine optimum distribution of brake torques including the regenerative brake torque for improving the braking energy recovery as well as the vehicle lateral stability. This cost function includes trade-off relation of two objectives. The physical meaning of first objective of cost function is to maximize the regenerative brake torque for improving the fuel economy and that of second objective is to increase the mechanical-friction brake torques at rear wheels rather than regenerative brake torque at front wheels for preventing front tire saturation. And weighting factor in cost function is also proposed as a function of under-steer index representing current state of the vehicle lateral motion in order to generalize the constrained optimization problem including both normal and severe cornering situation. For example, as the vehicle approaches its handling limits, adaptation of weighting factor is possible to prioritize front tire saturation over increasing the recuperation of braking energy for driver safety and vehicle lateral stability. Finally, computer simulation of closed loop driver-vehicle system based on Carsim? performed to verify the effectiveness of adaptation method in proposed controller and the vehicle performance of the proposed controller in comparison with the conventional controller for only considering the vehicle lateral stability. Simulation results indicate that the proposed controller improved the performance of braking energy recovery as well as guaranteed the vehicle lateral stability similar to the conventional controller.     

Combined control of a regenerative braking and antilock braking system for hybrid electric vehicles

Most parallel hybrid electric vehicles (HEV) employ both a hydraulic braking system and a regenerative braking system to provide enhanced braking performance and energy regeneration. A new design of a combined braking control strategy (CBCS) is presented in this paper. The design is based on a new method of HEV braking torque distribution that makes the hydraulic braking system work together with the regenerative braking system. The control system meets the requirements of a vehicle longitudinal braking performance and gets more regenerative energy charge back to the battery. In the described system, a logic threshold control strategy (LTCS) is developed to adjust the hydraulic braking torque dynamically, and a fuzzy logic control strategy (FCS) is applied to adjust the regenerative braking torque dynamically. With the control strategy, the hydraulic braking system and the regenerative braking system work synchronously to assure high regenerative efficiency and good braking performance, even on roads with a low adhesion coefficient when emergency braking is required. The proposed braking control strategy is steady and effective, as demonstrated by the experiment and the simulation.     

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.     

Experimental investigations on continuous regenerative anti-lock braking system of full electric vehicle

Functions of anti-lock braking for full electric vehicles (EV) with individually controlled wheel drive can be realized through conventional brake system actuating friction brakes and regenerative brake system actuating electric motors. To analyze advantages and limitations of both variants of anti-lock braking systems (ABS), the presented study introduces results of experimental investigations obtained from proving ground tests of all-wheel drive EV. The brake performance is assessed for three different configurations: hydraulic ABS; regenerative ABS only on the front axle; blended hydraulic and regenerative ABS on the front axle and hydraulic ABS on the rear axle. The hydraulic ABS is based on a rule-based controller, and the continuous regenerative ABS uses the gain-scheduled proportional-integral direct slip control with feedforward and feedback control parts. The results of tests on low-friction road surface demonstrated that all the ABS configurations guarantee considerable reduction of the brake distance compared to the vehicle without ABS. In addition, braking manoeuvres with the regenerative ABS are characterized by accurate tracking of the reference wheel slip that results in less oscillatory time profile of the vehicle deceleration and, as consequence, in better driving comfort. The results of the presented experimental investigations can be used in the process of selection of ABS architecture for upcoming generations of full electric vehicles with individual wheel drive.     

并联混合动力汽车驱动模式切换协调控制研究综述

混合动力汽车逐渐成为汽车行业发展的趋势,并已经在市场上取得了突破性的进展。混合动力系统中两动力源需要根据行驶路况进行能量管理和驱动模式的切换。由于发动机与电机动态响应特性的不同,单独按照各自的特性进行目标转矩控制,来达到总的需求转矩,但这样会导致整车运行模式切换过程中动力中断或出现转矩波动现象。本文主要研究运行模式切换过程中发动机与电机输出转矩的动态协调控制,目的是避免电机突增负载造成的震荡,希望在模式切换过渡过程中拥有足够的动力来保持整车快速、平稳行驶。     

Energy recovery based on pedal situation for regenerative braking system of electric vehicle

ABSTRACT

Energy recovery is a key technology to improve energy efficiency and extend driving range of electric vehicle. It is still a challenging issue to maximise energy recovery. We present an energy recovery mode (mode A) which recovers braking energy under all situations that accelerator pedal (AP) is lifted, brake pedal (BP) is depressed, as well as AP and BP are released completely; and propose a control strategy of regenerative braking based on driver's intention identified by a fuzzy recognition method. Other two modes: (1) recovery braking energy only the BP is depressed (mode B), (2) no energy recovery, have been studied to compare with mode A. Simulations are carried out on different adhesion conditions. Recovered energy and driving range are also obtained under FTP75 driving cycle. Road test is implemented to validate simulation results. Results show that mode A can improve energy recovery by almost 15.8% compared with mode B, and extend driving range by almost 8.81% compared with mode B and 20.39% with the mode of no energy recovery; the control strategy of regenerative braking can balance energy recovery and braking stability. The proposed energy recovery mode provides a possibility to achieve a single-pedal design of the electric vehicle.     

Powertrain design and experiment research of a parallel hybrid electric vehicle

The powertrain of an ultra-capacitor-based parallel hybrid electric vehicle (HEV) was developed. Innovations, such as the engine management system, floating ISG (Integrated Starter and Generator), electronic-controlled double-clutch system and dual-driven air conditioning system were realized. Hybrid control strategies to improve the fuel economy and reduce emissions were analyzed briefly. In order to ensure the vehicle emission performance, the engine management system calibration was performed. The vehicle emission test was also conducted, showing that the vehicle emission satisfied the EURO III standard and has great potential for improvement. The hybrid start test was introduced in detail. We realized the hybrid function and start parameter optimization of the engine and ISG.     

车用电涡流缓速器弯道制动的研究

推导出了装有电涡流缓速器的车辆在弯道制动过程中的运动微分方程,给出了制动时的理想制动力分配曲线公式,并以实车为例对缓速器在弯道上的制动性能进行了试验。     

Effect of drowsiness on driving performance variables of commercial vehicle drivers

Driver drowsiness is a major safety concern, especially among commercial vehicle drivers, and is responsible for thousands of accidents and numerous fatalities every year. The design of a drowsiness detection system is based on identifying suitable driver-related and/or vehicle-related variables that are correlated to the driver’s level of drowsiness. Among different candidates, vehicle control variables seem to be more promising since they are unobtrusive, easy to implement, and cost effective. This paper focuses on in-depth analysis of different driver-vehicle control variables, e.g., steering angle, lane keeping, etc. that are correlated with the level of drowsiness. The goal is to find relationships and to characterize the effect of a driver’s drowsiness on measurable vehicle or driving variables and set up a framework for developing a drowsiness detection system. Several commercial drivers were tested in a simulated environment and different variables were recorded. This study shows that drowsiness has a major impact on lane keeping and steering control behavior. The correlation of the number and type of accidents with the level of drowsiness was also examined. Significant patterns in lateral position variations and steering corrections were observed, and two phases of drowsiness-related degradation in steering control were identified. The two steering degradation phases examined are suitable features for use in drowsiness detection systems.     

Calibration efficiency improvement of rule-based energy management system for a plug-in hybrid electric vehicle

This paper presents a calibration method of a rule-based energy management strategy designed for a plug-in hybrid electric vehicle, which aims to find the optimal set of control parameters to compromise within the conflicting calibration requirements (e.g. emissions and economy). A comprehensive evaluating indicator covering emissions and economy performance is constructed by the method of radar chart. Moreover, a radial basis functions (RBFs) neural network model is proposed to establish a precise model within the control parameters and the comprehensive evaluation indicator. The best set of control parameters under offline calibration is gained by the multi-island genetic algorithm. Finally, the offline calibration results are compared with the experimental results using a chassis dynamometer. The comparison results validate the effectiveness of the proposed offline calibrating approach, which is based on the radar chart method and the RBF neural network model on vehicle performance improvement and calibrating efficiency.     

混合动力发动机与动力电池冷却余热双向循环预热

为了提高并联式混合动力汽车发动机和动力电池低温生存能力,探索发动机与电池冷却余热资源的利用新途径,提出了一种基于余热再利用的发动机和动力电池双向循环低温预热的新方法.建立发动机和动力电池余热数值模型,定量分析和研究余热系统的温升特点与温度分布状况,揭示了发动机与动力电池余热的传热规律,设计了基于相变材料的自动双向热控装...     

Improvement of drivability and fuel economy with a hybrid antiskid braking system in hybrid electric vehicles

When braking on wet roads, Antilock Braking System (ABS) control can be triggered because the available brake torque is not sufficient. When the ABS system is active, for a hybrid electric vehicle, the regenerative brake is switched off to safeguard the normal ABS function. When the ABS control is terminated, it would be favorable to reactivate the regenerative brake. However, recurring cycles from ABS to motor regenerative braking could occur. This condition is felt to be unpleasant by the driver and has adverse effects on driving stability. In this paper, a novel hybrid antiskid braking system using fuzzy logic is proposed for a hybrid electric vehicle that has a regenerative braking system operatively connected to an electric traction motor and a separate hydraulic braking system. This control strategy and the method for coordination between regenerative and hydraulic braking are developed. The motor regenerative braking controller is designed. Control of regenerative and hydraulic braking force distribution is investigated. The simulation and experimental results show that vehicle braking performance and fuel economy can be improved and the proposed control strategy and method are effective and robust.     

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.     

Examination of PN emissions and size distributions of a hybrid city bus under real world urban driving conditions

Engine load-speed frequency map of a hybrid city bus, which operates on the routes of Sakarya Municipality, was compared with that of European Transient Cycle (ETC) and World Harmonized Transient Cycle (WHTC), which are the certification test cycles. It was observed that the hybrid city bus engine operates mostly at three main regions, which are idling (30% load and 750 rpm), motoring (0% load and 1200 rpm) and high load (80% load and 1800 rpm) conditions under real world urban driving conditions. However, engine load-speed frequency maps of the certification test cycles are significantly different and cannot represent the real world urban driving conditions of the hybrid city bus. Therefore, the Particle Number (PN) emissions of the hybrid city bus were investigated under real world urban driving conditions. The aims of work were to examine the effects of city bus hybridization on the particle emissions and develop PN emission factors. The PN concentrations and size distributions together with engine operating conditions were measured with a Particle Measurement Program (PMP) compliant system, which involves a condensation particle counter (CPC) and a particle sizer (EEPS). The measurements under real world urban driving conditions indicated that the emission factors of the hybrid city bus for the PN and Total PN are 8.99E+12 and 2.51E+13 #/kW-h, respectively. The PN size distribution measurements indicated that the particles up to approximately 20 nm are not very sensitive to changes in engine power and they are exist even during motoring conditions. But, the particles in the size range from 20 to 200 nm are very sensitive to sudden changes of the engine power.     

Design of an energy management strategy for parallel hybrid electric vehicles using a logic threshold and instantaneous optimization method

A novel parallel hybrid electric vehicle (PHEV) configuration consisting of an extra one-way clutch and an automatic mechanical transmission (AMT) is taken as the study subject of this paper. An energy management strategy (EMS) combining a logic threshold approach and an instantaneous optimization algorithm is developed for the investigated PHEV. The objective of this EMS is to achieve acceptable vehicle performance and drivability requirements while simultaneously maximizing engine fuel economy and maintaining the battery state of charge (SOC) in its rational operation range at all times. Under the MATLAB/Simulink environment, a computer simulation model of the studied PHEV is established using the bench test results. Simulation results for the behavior of the engine, motor, and battery illustrate the potential of the proposed control strategy in terms of fuel economy and in keeping the deviations of SOC at a low level.     

Electrochemical battery model and its parameter estimator for use in a battery management system of plug-in hybrid electric vehicles

This paper reports the development of a battery model and its parameter estimator that are readily applicable to automotive battery management systems (BMSs). Due to the parameter estimator, the battery model can maintain reliability over the wider and longer use of the battery. To this end, the electrochemical model is used, which can reflect the aging-induced physicochemical changes in the battery to the aging-relevant parameters within the model. To update the effective kinetic and transport parameters using a computationally light BMS, the parameter estimator is built based on a covariance matrix adaptation evolution strategy (CMA-ES) that can function without the need for complex Jacobian matrix calculations. The existing CMA-ES implementation is modified primarily by region-based memory management such that it satisfies the memory constraints of the BMS. Among the several aging-relevant parameters, only the liquid-phase diffusivity of Li-ion is chosen to be estimated. This also facilitates integrating the parameter estimator into the BMS because a smaller number of parameter estimates yields the fewer number of iterations, thus, the greater computational efficiency of the parameter estimator. Consequently, the BMS-integrated parameter estimator enables the voltage to be predicted and the capacity retention to be estimated within 1 % error throughout the battery life-time.     

Effect of tumble-home on roof strength of a vehicle

This study reports on the effect of vehicle tumble-home (side body inclination) on roof strength. The steep inclination of the side body of a vehicle increases its roof strength. Comprehensive analysis of the impact of high roof strength driven by the steep inclination on dynamic roof strength in rollover is described. Here, we have developed a numerical model using the ADAMS, which is capable of characterizing both of the static and the dynamic roof strength. According to the FMVSS 216 protocol, we achieve the strength to weight ratio (SWR; static roof strength) by applying loading plates to the roof of a vehicle. The Controlled Rollover Impact System (CRIS) allows us to quantitatively characterize the displacements of the top end of A-pillar and B-pillar, thus determining the dynamic roof strength by comparing the results. We demonstrated that the roof intrusion was one of the most critical causes which lead to injuries of occupants fastening seat belts. Our analysis revealed that the increase of the side body inclination of vehicles enhanced the static roof strength whereas it could not reduce the roof displacement (intrusion) in the dynamic rollover.     

Vision-based fusion of robust lane tracking and forward vehicle detection in a real driving environment

With the goal of developing an accurate and fast lane tracking system for the purpose of driver assistance, this paper proposes a vision-based fusion technique for lane tracking and forward vehicle detection to handle challenging conditions, i.e., lane occlusion by a forward vehicle, lane change, varying illumination, road traffic signs, and pitch motion, all of which often occur in real driving environments. First, our algorithm uses random sample consensus (RANSAC) and Kalman filtering to calculate the lane equation from the lane candidates found by template matching. Simple template matching and a combination of RANSAC and Kalman filtering makes calculating the lane equation as a hyperbola pair very quick and robust against varying illumination and discontinuities in the lane. Second, our algorithm uses a state transfer technique to maintain lane tracking continuously in spite of the lane changing situation. This reduces the computational time when dealing with the lane change because lane detection, which takes much more time than lane tracking, is not necessary with this algorithm. Third, false lane candidates from occlusions by frontal vehicles are eliminated using accurate regions of the forward vehicles from our improved forward vehicle detector. Fourth, our proposed method achieved robustness against road traffic signs and pitch motion using the adaptive region of interest and a constraint on the position of the vanishing point. Our algorithm was tested with image sequences from a real driving situation and demonstrated its robustness.