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As electric vehicles become more widespread, such vehicles may be subject to “range anxiety” due to the risk of discharging during driving or the discharging when left unused for a long period. Accordingly, a vehicle equipped with a mobile charger that can provide a charge in an emergency. The vehicle with the mobile charger is usually composed of a large capacity battery, a power converter in a small truck. However, the large capacity battery and the power converter are disadvantageous in that they are large in size and expensive and should be produced as a special vehicle. In this paper, we propose a method to solve the problem using an internal EV system without requiring an additional power generation, battery and a charging-and-discharging device. The method is a novel Vehicle-to-Vehicle (V2V) fast charging control system utilizing motor and inverter in EV.

This paper suggests disturbance observer which improves performance of speed limit assist control. The nonlinear disturbance observer was designed so that disturbance caused by parameter and load uncertainties is able to be estimated exponentially. With the contribution of the observer, feed-forward and integral controllers can be omitted while improving steady-state error elimination and overshoot reduction. The acceleration observer is also designed to reduce the effect of wheel slip and changing slope. The performance of the controllers has been verified not only on flat roads, but also on wave road and rapidly changing ramps.

This paper presents an energy-optimal deceleration planning system (EDPS) to maximize regenerative energy for electrified vehicles on deceleration events perceived by map and navigation information, machine vision and connected communication. The optimization range for EDPS is restricted within an upcoming deceleration event rather than the entire routes while in real time considering preceding vehicles. A practical force balance relationship based on an electrified powertrain is explicitly utilized for building a cost function of the associated optimal control problem. The optimal inputs are parameterized on each computation node from a set of available deceleration profiles resulting from a deceleration time model which are configured by real-world test drivings.

This paper proposes a clutch control strategy during in-gear driving situations for Dual Clutch Transmissions (DCTs). The clutch is intentionally controlled to make small amount of a slip to identify the torque transfer capacity. The control objective of this phase is to ensure the clutch slip fairly remaining the specified value. To achieve this, the micro-slip controller is designed based on sliding mode control theory. Experimental verifications performed on onboard control system of the DCT equipped vehicle demonstrate that the proposed controller good tracking performance of the desired slip speed.

This paper presents the integrated chassis control(ICC) of four-wheel drive(4WD), electronic stability control(ESC), electronic control suspension(ECS), and active roll stabilizer(ARS) for limit handling. The ICC consists of three layers: 1) a supervisor determines target vehicle states; 2) upper level controller calculates generalized forces; 3) lower level controller, which is contributed in this paper, optimally allocates the generalized force to chassis modules. The lower level controller consists of two integrated parts, 1) longitudinal force control part (4WD/ESC) and 2) vertical force control part (ECS/ARS). The principal concept of both algorithms is optimally utilizing the capability of the each tire by monitoring tire saturation, with tire combined slip. By monitoring tire saturation, 4WD/ESC integrated system minimizes the sum of the tire saturation, and ECS/ARS integrated system minimizes the variance of the tire saturation.

Electro-Mechanical Brake (EMB) is the brake system that is actuated by electrical energy and has a similar design with the Electric Parking Brake (EPB). It uses motor power and gears to provide the necessary torque and a screw & nut mechanism is used to convert the rotational movement into a translational one. The main difference of EMB compared with EPB is that the functional requirements of components are much higher to provide the necessary performance for service braking such as response time. Such highly responsive and independent brake actuators at each wheel lead to enhanced controllability which should result in not only better basic braking performance, but also improvements in various active braking functions such as integrated chassis control, driver assistance systems, or cooperative regenerative braking.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.

A Software-in-the-Loop (SIL) simulation is presented here wherein control algorithms for the Anti-lock Braking System (ABS) and Roll Stability Control (RSC) system were developed in Simulink. Vehicle dynamics models of a 6×4 cab-over tractor and two trailer combinations were developed in TruckSim and were used for control system design. Model validation was performed by doing various dynamic maneuvers like J-Turn, double lane change, decreasing radius curve, high dynamic steer input and constant radius test with increasing speed and comparing the vehicle responses obtained from TruckSim against field test data. A commercial ESC ECU contains two modules: Roll Stability Control (RSC) and Yaw Stability Control (YSC). In this research, only the RSC has been modeled. The ABS system was developed based on the results obtained from a HIL setup that was developed as a part of this research.

After the second worldwide oil crisis, Brazil put in place by 1975 a strategic plan to stimulate the usage of ethanol (from sugar cane), to be mixed to the gasoline or to be sold as 100% ethanol fuel (known as E100). To enable an engine to operate with both gasoline and ethanol (and their mixtures), by 2003 the “Flex Fuel” technology was implemented. By 2012 calendar year, from a total of about 3.8 million vehicles sold in the Brazilian market, 91% offered the “Flex Fuel” technology, and great majority used a gasoline sub-tank to assist on cold starts (typically below 15°C, where more than 85% of ethanol is present in fuel tank). The gasoline sub-tank system suffers from issues such as gasoline deterioration, crash-worthiness and user inconvenience such as bad drivability during engine warm up phase. This paper presents fuel injector technologies capable of rapidly electrically heating the ethanol fuel for the Brazilian transportation market.

The effects of electrolyte on the cyclability of Li/S battery were investigated in this work. The electrochemical properties of single component ether solvents and a binary mixture of ether solvents were studied. These ether-based electrolytes have polysulfide shuttle problems which result in severe low Coulombic efficiency. To overcome these issues, sulfone-based solvent which forms a stable passivation film at the anode surface were used. As a result, the proper composition of sulfone-based electrolyte were obtained. Its capacity and reversible capacity retention were improved to 715 mAh/g and 72.6% which were increased by 52.1% and 63.1%, respectively, compared to those of ether-based electrolyte.

This paper proposes an effective nonlinear bicycle model including longitudinal, lateral, and yaw motions of a vehicle. This bicycle model uses a simplified piece-wise linear tire model and tire force tuning algorithm to produce closely matching vehicle trajectory compared to real vehicle for wide vehicle operation ranges. A simplified piece-wise tire model that well represents nonlinear tire forces was developed. The key parameters of this model can be chosen from measured tire forces. For the effects of dynamic load transfer due to sharp vehicle maneuvers, a tire force tuning algorithm that dynamically adjusts tire forces of the bicycle model based on measured vehicle lateral acceleration is proposed. Responses of the proposed bicycle model have been compared with commercial vehicle dynamics model (CarSim) through simulation in various vehicle maneuvers (ramp steer, sine-with-dwell).

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

Currently, the interest in accelerated reliability testing (ART) of electric vehicles parts has been increasing. In particular, an electric motor and battery are vital components of battery powered electric vehicles. The electric motor has two major roles, to discharge or charge battery when it is driven or braking. For analyzing the exact behavior mechanism of electric motor and predicting lithium-ion battery cell degradation, new accelerated reliability testing technology is required. This paper describes the results of research and development in new approach to reliability testing for electric vehicles. The methodology to measure a precise motor output torque of the rotating rotor using telemetry system was provided. The electric energy quantities as well as the used quantities of the electric power were also analyzed. The results of research and development in new approach to reliability testing for electric vehicles were systematized and reflected in development.

A nano-sized PM and THC emission characteristics were investigated according to the fuel injection strategy such as a pressure and timing in the GDI engine. On the part-load condition, the particulate emissions exhibited a strong sensitivity to the injection timing. The fuel injection pressure also had a great association with the nano-particles and THC. A size of PM exhausted from the GDI engine located near 10nm on the part-load. In contrast, accumulation mode particles within 60 - 80nm mainly exhausted during the cold transient start phase. Increment of fuel injection pressure positively affected on the nano-particle and THC emissions during the start of the engine, as well.

Wide attention to fuel cell electric vehicles (FCEVs) comes from two huge issues currently the world is facing with: the concern of the petroleum reserves depletion due to consequent oil dependence and the earth global warming due in some extent to vehicle emissions. In this background, Hyundai, along with its sister company Kia, has been building the FCEVs and operating their test fleet with several tens of units at home and abroad. Since 2004, 32 passenger vehicles have been offered for the Department of Energy's controlled hydrogen fleet and infrastructure demonstration and validation project in the U.S. In the meantime, from 2006, 30 passenger vehicles as well as four buses, featuring the in-house developed fuel cell stack and its associated components, are currently under the domestic operation for the FCEV learning demonstration led by the Ministry of Knowledge and Economy.

Due to aging of a battery over lifetime, the rated power and nominal energy capacity will be reduced compared with the initial rated power and capacity. These result in influences on the vehicle driving performance and fuel economy. To monitor and diagnose the aging of the battery, in this paper, the method of predicting the available rated power and energy capacity of Li-ion battery under in-vehicle condition is proposed. Under constant power test, available power is calculated from the estimated parameters using recursive least square method. Further, available energy capacity is evaluated through SOH(cn) defined by the ratio of initial state-of-charge (SOC) variation to present SOC (\GdSOC ⁿ /ΔSOC ⁿ ) variation under arbitrary in-vehicle driving cycles. To verify the proposed method, experiments for aging Li-ion battery are performed in hybrid electric vehicle.

The series-parallel hybrid electric vehicle(HEV), which employs a planetary gear set to combine one internal combustion engine(ICE) and two electric motors(EMs), can take advantages of both series and parallel hybrid system. The efficient powertrain operating point of the system can be obtained by the instantaneous optimization of equivalent fuel consumption. However, heavy computational requirements and variable constraints of the optimization process make it difficult to build real-time control strategy. To overcome the difficulty, this study suggests the control strategy which divides the optimization process into 2 stages. In the first stage, a target of charge/discharge power is determined based on equivalent fuel consumption, then in the second stage, an engine operating point is determined taking power transfer efficiency into account.

A determination of the vehicle states and tire forces is critical to the stability of vehicle dynamic behavior and to designing automotive control systems. Researchers have studied estimation methods for the vehicle state vectors and tire forces. However, the accuracy of the estimation methods is closely related to the employed model. In this paper, tire lag dynamics is introduced in the model. Also application of estimation methods in order to improve the model accuracy is presented. The model is developed by using the global searching algorithm, a Genetic Algorithm, so that the model can be used in the nonlinear range. The extended Kalman filter and sliding mode observer theory are applied to estimate the vehicle state vectors and tire forces. The obtained results are compared with measurements and the outputs from the ADAMS full vehicle model. [15]