Browse Topic: Stop / start technology
Linear time-invariant (LTI) reduced-order models (ROMs) have been widely used in battery thermal management simulations due to their low hardware requirements, high computational efficiency, and good accuracy. However, the inherent assumption of LTI behavior limits their applicability in scenarios with varying coolant flow rates, where this assumption is no longer valid. To address this limitation, a novel ROM is developed by decomposing the entire battery thermal system into two subsystems. All solid components are modeled as a traditional LTI ROM, while the coolant channel is represented using Newton’s cooling law. The two subsystems are then coupled through the exchange of heat transfer rate and temperature at the fluid–solid interface between the coolant and the cold plate. Model fidelity is further enhanced by introducing a spatially distributed heat flux during the generation of the LTI ROM for solid components. Validation is performed against CFD simulations at both module and pack levels, under constant and varying flow rates. The results demonstrate that the proposed ROM achieves high accuracy while requiring several orders of magnitude less computational time than the corresponding CFD models.
In recent years, computer-aided engineering (CAE) has become an essential practice in design and durability analysis of industrial components such as weldments. The current analytical trend for CAE-based fatigue life prediction of weldments includes procedures based on design guidelines, mesh-sensitive methods (e.g., local strain-life approach) and mesh insensitive methods (e.g., Volvo and Verity methods). As an inherent characteristic of weldments, the geometry of the weld is often simplified in failure analysis and important hotspots such as start/stop of the weld beads are not considered in the design process. However, such critical locations cannot be avoided in complex welded structures. Therefore, incorporating main geometrical details of the weld can improve the accuracy of critical regions identification and damage calculation using mesh-sensitive CAE-based methodologies. Herein, a framework for life prediction of welded components including the weld geometry is discussed and evaluated by its application to a coupled torsion beam axle. The weldment was simulated in finite element (FE) environment as a shell model with local mesh refinement and improved weld geometry. The FE model was validated by strain gage measurements of the actual component under single-channel constant amplitude load and critical locations in the component were accurately identified. Local stress-life and critical plane approaches were employed to predict fatigue life to failure resulting in reasonable accuracy within a factor of two. Despite the close results by the uniaxial and multiaxial fatigue damage criteria in this work, advanced life prediction approaches such as the critical plane concept are recommended due to their robustness for more complex and realistic loading conditions during service.
Commercial transportation is the key pillar of any growing economy. Light and Small commercial vehicles are increasing every day to cater the logistics demand, but there is always a gap between customer’s actual and desired operational efficiency. This is because of lack of organized fleet and efficient fleet operation. The major requirement of fleet owners is timely delivery, high productivity, downtime reduction, real time tracking, etc., Automakers are now providing fleet management application in modern LCV & SCV to satisfy the fleet operator requirement. However, any feature malfunction, consignment mismatch, wrong notification, missed alerts, etc., can incur huge loss to fleet operator and disrupt the entire supply chain. Hence it is very critical to extensively validate the telematics features in fleet management application. This paper explains the approach for exhaustive validation strategy of fleet management applications (B2B) from end user perspective. An effective test methodology was established to validate every feature against the real-world possibilities and actual data (CAN/sensor values). Key feature such as Consignment Assignment can be verified by recreating all real-world circumstances such as different delivery scenario, consignment pickup scenario, breakdown scenario, true testing, mock testing, consignment transfer in case of breakdown, partial consignment delivery scenario, etc. The driver and vehicle efficiency mapping feature such as Mileage monitoring, driver monitoring, scheduled maintenance, fuel logs, trip logs can be verified by recreating all customer and field use cases. All the location and real time tracking based features are verified against the instrumented Geo position sensors. Vehicle-based alerts such as idle alert, start stop alert, overspeed, door alert, etc., can be verified against the vehicle logger data values. Lastly, the User interface and user experience of the application is also validated up to icon level in every screen, to ensure ease of use and adaptability for the customer. Thus, an innovative and customer centric approach is established to validate Telematics feature for fleet customers, which is robust and time efficient.
Cummins announced its seventh-generation series HE250 and HE300 waste-gate turbochargers for medium displacement on- and off-highway commercial engines. The turbos are sized for 5.5- to 8-liter medium-duty diesel engines and 8- to 11-liter natural-gas engines. Cummins states that the HE250 and 300 were designed to meet the global emissions regulations from 2024 onwards including the upcoming China Stage IV FE 2024, NSVII 2026 and Euro VII 2027. Cummins claims significant improvements in performance and durability compared to the outgoing models. Both turbos reportedly offer a 6-7% gain in overall efficiency as well as enhanced low-speed performance, which translates to additional low-end torque and better compatibility with engine start/stop systems.
As the electrification of automobiles continues to accelerate, the need for a safe, reliable, high-power energy-storage technology is greater than ever. Ultracapacitors already have an established place in Voltage Stabilization Systems (VSS) for internal-combustion engine (ICE) stop-start applications. By providing additional voltage support during a high-current cranking event, voltage levels are maintained to allow proper operation of accessories without interruption and enable proper operation as battery state-of-health declines.
This SAE Information Report SAE J2836/5 establishes the Use Cases for communications between plug-in electric vehicles (PEVs) and their customers. The Use Case Scenarios define the information to be communicated related to customer convenience features for charge on/off control, charge power curtailment, customer preference settings, charging status, EVSE availability/access, and electricity usage. Also addresses customer information resulting from conflicts to customer charging preferences. This document only provides the Use Cases that define the communications requirements to enable customers to interact with the PEV and to optimize their experience with driving a PEV. Specifications such as protocols and physical transfer methods for communicating information are not within the scope of this document.
In the current situation and upcoming government regulations, hybrid vehicles are very promising in terms of meeting fuel economy and stringent requirements of emission norms. Herein, hybridization will be mostly done with gasoline and CNG vehicles. As a normal practice, engine is switched off at the signal and again restart with engine start-stop technology. So, instances of engine start/stop are increased in hybrid vehicle in comparison with standard IC engine vehicle. In order to achieve smooth engine start, engine starting torque can be optimized by adjusting engine valve timing. As Electric Cam Phaser (ECP) meets valve timing target even before first engine combustion start, this is one of the critical technologies in reducing engine starting torque and time reaching to idle speed. This engine starting strategy also gives benefits in terms of reducing engine start emissions and improving fuel economy. This paper describes selection of electric cam phaser for hybrid vehicle depending on specific engine starting and vehicle requirements. In addition to this, engine starting vibration is very critical, as its frequency increases due to multiple engine start/stop operation in hybrid vehicle either on traffic signal or on smooth highways. This work also shows detail understanding of engine start vibrations and ECP strategy to reduce these vibrations by optimizing engine valve timing.
In this work, a dynamically loaded hydrodynamic journal bearing test rig is developed and introduced. The rig is a novel design, using a hydraulic actuator with fast acting spool valves to apply load to a connecting rod. This force is transmitted through the connecting rod to the large end bearing which is mounted on a spinning shaft. The hydraulic actuator allows for fully variable control and can be used to apply either static load in compression or tension, or dynamic loading to simulate engine operation. A variable speed electric motor controls shaft speed and is synchronized to the hydraulic actuator to accurately simulate loading to represent all four engine strokes. A high precision torque meter enables direct measurements of friction torque, while shaft position is measured via a high precision encoder. Data generated on the test rig is also presented, and includes frictional torque loss, cumulative energy consumption during transient operation, and starting energy during stop/start testing.
As computer-aided engineering software tools advance, more simulation-based processes are utilized to reduce development time and cost. Traditionally, during the development of a new control algorithm dyno or on-road testing is necessary to validate a new function, however, physical testing is both costly and time consuming. This study introduces a co-simulation platform and discusses its use as an improved method of powertrain control logic development. The simulation platform consists of a dynamic vehicle model, virtual road network and simulated traffic objects. Engineers can utilize Matlab/Simulink along with other programs such as PTV Vissim, Tass Prescan, and AVL Cruise to create an integrated platform capable of testing and validating new control strategies. The structure and configuration of this virtual platform is explained in this paper, and an example use case is demonstrated. A driver model was developed to simulate realistic vehicle inputs. Validation of this new driver model utilized different intersection types, speed limits, traffic signs, and traffic conditions. A smart Engine Start/Stop control algorithm was implemented and tested by using the platform under different real-world driving conditions. It was demonstrated that with a validated driver model, the new virtual platform could be used to test and validate control algorithms under a variety of scenarios.
The definition of the energy management strategy for a hybrid electric vehicle is a key element to ensure maximum energy efficiency. The ability to optimally manage the on-board energy sources, i.e., fuel and electricity, greatly affects the final energy consumption of hybrid powertrains. In the case of plug-in series-hybrid architectures, such as Range-Extender Electric Vehicles (REEVs), fuel efficiency optimization alone can result in a stressful operation of the range-extender engine with an excessively high number of start/stops. Nonetheless, reducing the number of start/stops can lead to long periods in which the engine is off, resulting in the after-treatment system temperature to drop and higher emissions to be produced at the next engine start. In this work, Dynamic Programming is used to define the optimal energy management strategy for the REEV with a multi-objective cost function that takes into account not only fuel consumption, but also engine start/stops and pollutant emissions. To this aim, experimental data has been used to estimate emissions and develop a thermal model for the after-treatment system. Specifically, a Class 6 pick-up and delivery truck with a plug-in series-hybrid architecture has been modeled in a backward simulator using experimental performance maps. The results show that the optimal energy management strategy with respect to fuel consumption alone is a “blended” strategy. Conversely, the optimal strategy for minimum emissions and reduced start/stops is found to be a charge-depleting (pure electric) strategy with a one-time recharge. When the conflicting objectives of minimum fuel consumption, low number of engine start/stops, and reduced emissions are included in a single cost function for multi-objective optimization, the results show that a trade-off solution can be selected, for which the fuel consumption is near-optimal (less than 5% increase), the engine start/stops are low, and the pollutant emissions are reduced (by more than 50%).
Diesel engine cold start is emerging as a critical topic of investigation. Of key importance is the impact the warm-up period has on particulate emissions. Presented in this work is a fundamental and comprehensive study on the impact of cold, warm, and hot start on particulate emissions over a custom quasi-steady-state drive cycle discretized by frequent engine stop/start. The experiments were conducted on a six-cylinder, turbocharged, diesel engine. Compared with cold start, the count median diameter (CMD) increased by 16% and 5% in the Aitken mode at 1500 rpm and 2000 rpm, respectively, when the engine was fully warmed up. The geometric standard deviation (GSD) decreased as the engine warmed up. Particle number (PN) concentration decreased by 50% as the engine coolant temperature reached 70°C, compared to cold start (23°C), and a strong positive linear correlation was found between the particle mass (PM) and PN emissions at all loads. This work explores the topic of engine warm-up with respect to particulate emissions with a rigor not previously done.
The three-way-catalyst (TWC) is an essential part of the exhaust aftertreatment system in spark-ignited powertrains, converting nearly all toxic emissions to harmless gasses. The TWC’s conversion efficiency is significantly temperature-dependent, and cold-starts can be the dominating source of emissions for vehicles with frequent start/stops (e.g. hybrid vehicles). In this paper we develop a thermal TWC model and calibrate it with experimental data. Due to the few number of state variables the model is well suited for fast offline simulation as well as subsequent on-line control, for instance using non-linear state-feedback or explicit MPC. Using the model could allow an on-line controller to more optimally adjust the engine ignition timing, the power in an electric catalyst pre-heater, and/or the power split ratio in a hybrid vehicle when the catalyst is not completely hot. The model uses a physics-based approach and resolves both axial and radial temperature gradients, allowing for the thermal transients seen during heat-up to be represented far more accurately than conventional scalar (i.e. lumped-temperature) real-time models. Furthermore, we also use a physics-based chemical kinetics reaction model for computing the exothermic heat of reaction and emission conversion rate which is temperature and residence-time-dependent. We have performed an experimental campaign with a standard spark-ignited engine and a commercial TWC, where we measured steady-state operation and cold-start transient behavior. This experimental data allowed us to tune the model, where we found excellent matching between the measured and modeled tailpipe emissions. Modeling the radial temperature gradient improved the relative accuracy of the conversion efficiency by 15%, and simulations indicate the potential for an absolute improvement by 15 percentage points for some cases. Furthermore, the modeled TWC temperature evolution for a cold-start was typically within ±10 ° C of the measured temperature (with a maximal deviation of 20 °C). The proposed model thus bridges a gap between heuristic models suited for on-line control and accurate models for slower off-line simulation.
Electronic Stop-Start (ESS) system automatically stops and restarts the engine to save energy, improve fuel economy and reduce emissions when the vehicle is stationary during traffic lights, traffic jams etc. The stop and start events cause unwanted vibrations at the seat track which induce discomfort to the driver and passengers in the vehicle. These events are very short duration events, usually taking less than a second. Time domain analysis can help in simulating this event but it is difficult to see modal interactions and root cause issues. Modal transient analysis also poses a limitation on defining frequency dependent stiffness and damping for multiple mounts. This leads to inaccuracy in capturing mount behavior at different frequencies. Most efficient way to simulate this event would be by frequency response analysis using modal superposition method. In order to do the same, there is a major hurdle which is due to the nature of the signal being highly transient and of short duration, this event is difficult to be captured in frequency domain. Traditional FFT techniques used for domain transformation are not accurate enough to capture and transform these short duration events from time domain to frequency domain and vice-versa. Simulation in frequency domain helps in interpreting the effects of modal interactions and resonances. It also helps in providing enablers to mitigate issues and use frequency dependent stiffness for mounts and appropriate damping. This paper focuses on providing a comprehensive method to capture this short duration transient ESS start event in frequency domain accurately, by using Discrete Fourier Transform (DFT) along with additional modifications to the mathematical formulation. This paper also highlights the boundary conditions required to accurately simulate this event for different suspension architectures for instance solid axle suspensions and independent suspensions. Finally, this paper also showcases test vs virtual correlation case studies for ESS virtual analysis of a full vehicle system with different suspension architectures.
National concerns over energy consumption and emissions from the transportation sector have prompted regulatory agencies to implement aggressive fuel economy targets for light-duty vehicles through the U.S. National Highway Traffic Safety Administration/Environmental Protection Agency (EPA) Corporate Average Fuel Economy (CAFE) program. Automotive manufacturers have responded by bringing competitive technologies to market that maximize efficiency while meeting or exceeding consumer performance and comfort expectations. In a collaborative effort among Toyota Motor Corporation, Argonne National Laboratory (ANL), and the National Renewable Energy Laboratory (NREL), the real-world savings of one such technology is evaluated. A commercially available Toyota Highlander equipped with two-phase cold storage technology was tested at ANL’s chassis dynamometer testing facility. The cold storage technology maintains the thermal state of air-conditioning evaporators to enable longer and more frequent engine-off operation in vehicles equipped with start-stop functionality. Test results were analyzed and provided to NREL where a novel simulation framework was developed and calibrated to the test data. The vehicle model was then exercised over a large set of real-world drive cycle and ambient condition data to estimate national-level fuel economy benefits. Results indicate that the cold storage evaporator provided national fuel consumption reductions of 0.1124% relative to a conventional evaporator in the same vehicle. In addition, when the cold storage evaporator engine stop/start was enabled for any temperature and the baseline was limited to the EPA menu, Start and Stop credit assumption of 27°C, a national fuel savings of 0.3724% was found. Fuel savings resulted from a combination of extended engine-off duration during idle events and increased frequency of deceleration fuel cutoff, both enabled by the ability of the cold storage evaporator to maintain thermal state in situations where air conditioning is active.
Battery models are being developed as a component of the powertrain systems of hybrid electric vehicles (HEVs) to predict the state of charge (SOC) accurately. Electrically heated catalysts (EHCs) can be employed in the powertrains of HEVs to reach the catalyst light off temperature in advance. However, EHCs draw power from the battery pack and hence sufficient energy needs to be stored to power auxiliary components. In series HEVs, the engine is primarily used to charge the battery pack. Therefore, it is important to develop a control strategy that triggers engine start/stop conditions and reduces the frequency of engine operation to minimize the equivalent fuel consumption. In this study, a battery pack model was constructed in MATLAB-Simulink to investigate the SOC variation of a high-power lithium ion battery during extreme engine cold start conditions (-7°C) with/without application of an EHC. The EHC was simulated in MATLAB to determine the energy required to heat the catalyst during cold start conditions. The effect of the EHC in emissions purification at -7°C was studied using a three-way catalyst (TWC) model. The EHC was operated only during the initial few seconds before the engine start to increase the bed temperature of the catalyst. This was found to have a significant impact on exhaust gas emissions even under cold start conditions. However, powering the EHC lowered the SOC of the battery pack, triggering the engine to run and consume more fuel. Hence, an engine ON/OFF control strategy was proposed to control the engine operation conditions and effectively charge the battery pack. The SOC variation of the battery pack and the effects on emissions and fuel consumption were simulated and compared with/without the EHC. The battery model was validated with a control strategy proposed in simulations at 23°C and a parameter study was conducted at -7°C.
Modern hybrid technologies, especially mild and micro-hybrids with auto start/stop feature, demand a starter with higher power, better performance and longer life than conventional brush-type starters. In this paper, a new starter design using a brushless motor is proposed. This improves the engine crank performance during autostarts due to lower inertia, higher torque and wider power band capability of the brushless motor, especially at higher speeds. The overall integrated system includes the motor, inverter and controller all packaged in the same form factor of the original starter housing as a “drop-in replacement”. The prototype starter motor is designed to operate at 48V with a peak power of 4kW but can be designed to operate at the standard 12V. This paper will describe in detail the functionalities of the overall system and the simulation and experimental results of the prototype that was tested on a 4-cylinder engine in a production crossover vehicle.
Idle Stop-and-go (ISG), also known as Auto Stop/Start, is a fuel saving technology common to many modern vehicles that enables the engine to shut down when the vehicle comes to a stop. Although it may help with fuel efficiency, many drivers in the North American market find the feature to be an annoyance due to hesitation in vehicle re-launch and engine shudder during stop or restart. This paper introduces the usage of traffic signal phase and timing (SPaT) information for controlling the activation of ISG with the goal of reducing driver complaints and increasing acceptance of the function. Previous studies proposed the utilization of Advanced Driver Assistance System (ADAS) to introduce adaptability in powertrain controls to traffic situation changes. For instance, when a vehicle stops and the engine shuts off, the controller monitors the movement of the preceding vehicle using ADAS sensors and restarts the engine when the front launches, prior to the driver releasing the brake pedal. The control logic can also utilize the traffic sign recognition function of the vision sensor to inhibit ISG under specific driving conditions where the feature is typically undesirable, for example, while stopped at a stop sign or waiting at a roundabout. However, when the vehicle is first in line at a traffic light, the previously suggested method for engine restart based on movement detection becomes useless because there is no target vehicle ahead to follow. Thus, the new control logic proposed in this paper leverages Vehicle-to-Infrastructure (V2I) communication for engine restart out of ISG. By obtaining the SPaT of a traffic light, the engine can be restarted a couple of seconds before the traffic light turns green without having to observe a preceding vehicle’s movement. Two methods for obtaining SPaT information were investigated. The first used a smart phone connected to a traffic information server via a 4G LTE network, and the second used Dedicated Short Range Communication (DSRC). Both of these methods showed that this advanced control strategy provides readiness for forthcoming vehicle launch, which may promote acceptance of the ISG function. The description of the new control logic is discussed, and the validation results acquired through real-world vehicle tests are demonstrated.
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