Active coolant control strategies in automotive engines

The coolant flow rate in conventional cooling systems in automotive engines is subject to the mechanical water pump speed, and high efficiency in terms of fuel economy and exhaust emission is not possible given this limitation. A new technology must be developed for engine cooling systems. The electronic water pump is used as a substitute for the mechanical water pump in new engine cooling systems. The new cooling system provides more flexible control of the coolant flow rate and engine temperature, which previously relied strongly on engine driving conditions such as load and speed. In this study, the feasibility of two new cooling strategies was investigated using a simulation model that was validated with temperatures measured in a diesel engine. Results revealed that active coolant control using an electronic water pump and valves substantially contributed to a reduction of coolant warm-up time during cold engine starts. Harmful emissions and fuel consumption are expected to decrease as a result of a reduction in warm-up time.     

Transient modeling and validation of lithium ion battery pack with air cooled thermal management system for electric vehicles

A transient numerical model of a lithium ion battery (LiB) pack with air cooled thermal management system is developed and validated for electric vehicle applications. In the battery model, the open circuit voltage and the internal resistance map based on experiments are used. The Butler-Volmer equation is directly considered for activation voltage loss estimation. The heat generation of cells and the heat transfer from cells are also calculated to estimate temperature distribution. Validations are conducted by comparison between experimental results at the cell level and the pack level. After validations, the effects of module arrangement in a battery pack are studied with different ambient temperature conditions. The configuration that more LiB cells are placed near the air flow inlet is more effective to reduce the temperature deviation between modules.     

Structural Optimization for Roof Crush Test Using an Enforced Displacement Method

A roof crush test has been utilized to reduce passengers’ injuries from a vehicle rollover. The Federal Motor Vehicle Safety Standards (FMVSS) 216 and the Insurance Institute for Highway Safety (IIHS) perform actual vehicle tests and evaluate the vehicle’s ratings. Nonlinear dynamic response structural optimization can be employed not only for achievement of a high rating but also minimization of the weight. However, the technique needs a huge computation time and cost because many nonlinear dynamic response analyses are required in the time domain. A novel method is proposed for nonlinear dynamic response structural optimization regarding the roof crush test. The process of the proposed method repeats the analysis domain and the design domain until the convergence criteria are satisfied. In the analysis domain, the roof crush test is simulated using a high fidelity model of nonlinear dynamic finite element analysis. In the design domain, a low fidelity model of linear static response structural optimization is utilized with enforced displacements that come from the analysis domain. Correction factors are employed to compensate the differences between a nonlinear dynamic analysis response and a linear static analysis response with enforced displacement. A full-scale vehicle problem is optimized with a constraint on the rigid wall force from the analysis in the design domain.     

Requirement-based testing of an automotive ECU considering the behavior of the vehicle

HILS (Hardware In the Loop Simulation) and RBT (Requirement-Based Testing) are widely used to evaluate the performance and reliability of automotive ECUs (Electronic Control Units). The HILS method is used to predict the behavior of ECU-installed vehicles and to evaluate the performance of ECU controllers. RBT evaluates whether the embedded system satisfies the pre-defined requirements. In this study, the behavior of a vehicle is regarded as a system requirement, and an embedded system test procedure that evaluates the system requirement is proposed. In particular, a new method is introduced, which integrates HILS with RBT. Using the proposed method, the behavior of an articulated vehicle equipped with an AWS (All Wheel Steering) ECU is evaluated with RBT software.     

Torque control of engine clutch to improve the driving quality of hybrid electric vehicles

As a powertrain for hybrid electric vehicles (HEVs), the automatic transmission (AT) is not only convenient for the driver but also reduces hybridization costs because the existing production line is used to produce the AT. However, it has low fuel economy due to the torque converter. To overcome this disadvantage, this paper studies HEVs equipped an AT without a torque converter. In this case, additional torque control is needed to prevent the driving quality from deteriorating. This paper suggests three different torque control methods and develops a simulator for an HEV that can simulate the dynamic behaviors of the HEV when the engine clutch is engaged. The HEV drive train is modeled with AMESim, and a controller model is developed with MATLAB/Simulink. A co-simulation environment is established. By using the developed HEV simulator, simulations are conducted to analyze the dynamic behaviors of the HEV according to the control methods.     

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.     

Adaptive neural network based fuzzy control for a smart idle stop and go vehicle control system

Idle stop and go (ISG) is a low cost but very effective technology to improve fuel efficiency and reduce engine emissions by preventing unnecessary engine idling. In this study, a new method is developed to improve the performance of conventional ISG by monitoring traffic conditions. To estimate frontal traffic conditions, an ultra-sonic ranging sensor is employed. Several fuzzy logic algorithms are developed to determine whether the engine idling is on or off. The algorithms are evaluated experimentally using various data gathered in real areas with traffic congestion. The evaluation results show that the method developed can reduce the chance of false application of ISG significantly while improving fuel efficiency up to 15%.     

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.     

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.