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Concerns about climate change have significantly accelerated the process of vehicle electrification to improve the sustainability of the transportation sector. Increasing the adoption of electrified vehicles is closely tied to the advancement of reliable energy storage systems, with lithium-ion batteries currently standing as the most widely employed technology. One of the key technical challenges for reliability and durability of battery packs is the ability to accurately predict and control the temperature of the cells and temperature gradient between cells inside the pack. For this reason, accurate models are required to predict and control the cell temperature during driving and charging operations. This work presents a set of procedures tailored to characterize and measure the thermal properties in li-ion cells and modules.

Electrification of vehicles is an important step towards making mobility more sustainable and carbon-free. Hybrid electric vehicles use an electric machine with an on-board energy storage system, in some form to provide additional torque and reduce the power requirement from the internal combustion engine. It is important to control and optimize this power source split between the engine and electric machine to make the best use of the system. This paper showcases an implementation of the Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) with minimization in real-time in the dSPACE MicroAutobox II as the Hybrid Supervisory Controller (HSC). While the concept of A-ECMS has been well established for many years, there are no published papers that present results obtained in a production vehicle suitably modified from conventional to hybrid electric propulsion including real world testing as well as testing on regulatory cycles.

Battery packs used in automotive application experience high-power demands, fast charging, and varied operating conditions, resulting in temperature imbalances that hasten degradation, reduce cycle life, and pose safety risks. The development of proper simulation tools capable of capturing both the cell electrical and thermal response including, predicting the cell’s temperature rise and distribution, is critical to design efficient and reliable battery packs. This paper presents a co-simulation model framework capable of predicting voltage, 2-D heat generation and temperature distribution throughout a cell. To capture the terminal voltage and 2-D heat generation across the cell, the simulation framework employs a high-fidelity electrical model paired with a charge balance model based on the Poisson equation. The 2-D volumetric heat generation provided by the charge balance model is used to predict the temperature distribution across the cell surface using CFD software.

Reducing computational time has become a critical issue in recent years, particularly in the transportation field, where the complexity of scenarios demands lightweight controllers to run large simulations and gather results to study different behaviors. This study proposes two novel formulations of the Optimal Control Problem (OCP) for the Energy Management System of a Plug-in Hybrid Electric Vehicle (PHEV) and compares their performance with a benchmark found in the literature. Dynamic Programming was chosen as the optimization algorithm to solve the OCP in a Matlab environment, using the DynaProg toolbox. The objective is to address the optimality of the fuel economy solution and computational time. In order to improve the computational efficiency of the algorithm, an existing formulation from the literature was modified, which originally utilized three control inputs.

Backlash is the movement between the gear teeth that allows them to mate without binding. Backlash can cause large torque fluctuations in vehicle powertrains when the input torque changes direction. These fluctuations cause a jerk and shuddering, which negatively affects drive quality. Input torque frequently changes direction in electric vehicles due to regenerative braking. Limiting zero crossings is an option for better drive quality; however, this leads to decreased vehicle efficiency. Because of this, modulating the torque through the backlash region is preferred, yet, if done poorly, it can result in sluggish torque response. This paper proposes a torque-shaping algorithm for an electric motor and gear/differential system to reduce backlash in electric vehicles. The control algorithm modulates the commanded torque’s rate of change based on the vehicle speed and zero-crossing torque.

Electrification is getting more important in the aviation industry with the increasing need for reducing emissions of carbon dioxide and fuel consumption. It is crucial to assess the behavior of Li-Ion batteries at high-altitude conditions to design safe and reliable battery packs. This paper aims at benchmarking the performance of different formats of battery cells (pouch cells and cylindrical cells) in low-pressure environments. A test setup was designed and fabricated to replicate the standard procedure defined by the RTCA DO-311 standard, such as the altitude test and rapid decompression test. During the test voltage, current, temperature, and pressure were monitored, and the evaluation criteria is based on the capacity retention, along with the structural integrity of the cell. From preliminary tests, it was observed that cylindrical cells do not show a significant change in performance at low-pressure conditions thanks to their steel casing.

The battery electric vehicle (EV) industry has experienced considerable growth over the last few years, demonstrating a clear acceleration in adoption and deployment. However, there are still many questions concerning what will happen to batteries as they reach their end of life (EOL), as batteries that have “aged out” can either be reused, recycled, or go to a landfill. Final Disposition of Electric Vehicle Batteries addresses some unsettled issues around lithium-ion battery reuse and recycling. Insufficient investment and regulations are a current barrier to a robust reuse system, and safety concerns potentially hinder adoption. Despite the benefits of battery recycling, there are also many challenges when considering their transportation and disassembly. These challenges will need to be addressed as the industry sees an influx of EV batteries reaching their EOL within the next 10 years. Click here to access the full SAE EDGETM Research Report portfolio.

Simulation-based design of connected and automated hybrid-electric vehicles is a challenging problem. The design space is large, the systems are complex, and the influence of connected and autonomous technology on the process is a new area of research. The Ohio State University EcoCAR Mobility Challenge team developed a comprehensive design and simulation approach as a solution. This paper covers the detailed simulation work conducted after initial design space reduction was performed to arrive at a P0-P4 hybrid vehicle with a gasoline engine. Two simulation environments were deployed in this strategy, each with unique advantages. The first was Autonomie, which is a commercial software tool that is well-validated through peer-reviewed studies. This allowed the team to evaluate a wide range of components in a robust simulation framework.

Carla Bailo, CEO of the Center for Automotive Research, and Terry Barclay, CEO of Inforum, bring together over 30 of the most influential women in the automotive industry to share their insight and advice. From suppliers to OEMs, they hail from every corner of the industry. Readers will learn how to take charge of their own careers by understanding the experiences of these professionals. Topics include: • Work-Life Integration - How can you be whole at home, at work, and in the community? • Education and Lifelong Learning - Do you really need a graduate degree? • Mentor and Sponsor Relationships - How do you find mentors and sponsors and form productive relationships with them? • Career Challenges - How do you evaluate when to take career risks? How do you say yes when all the boxes aren't checked? • Resilience - Where do you find the internal fortitude to keep going? • Personal Satisfaction - What do these leaders find most joyful about their careers?

The Chevy Bolt’s One Pedal Driving feature is a new electrification propulsion enhancement that allows the driver to accelerate, decelerate and hold their vehicle stationary by just using the accelerator pedal. With this new feature, the driver is relieved of having to switch between pressing the accelerator pedal and brake pedal to slow, stop and hold the vehicle stationary. While this feature provides a convenience to the driver, it also presents a paradigm shift in driver engagement and control system responsibility for executing certain functions that the driver was traditionally responsible to perform. Various system safety techniques were involved in the development of such a feature both from a traditional functional safety perspective as well as a Safety of the Intended Functionality (SOTIF) perspective.

There is an increasing interest in transient thermal simulations of automotive brake systems. This paper presents a high-fidelity CFD tool for modeling complete braking cycles including both the deceleration and acceleration phases. During braking, this model applies the frictional heat at the interface on the contacting rotor and pad surfaces. Based on the conductive heat fluxes within the surrounding parts, the solver divides the frictional heat into energy fluxes entering the solid volumes of the rotor and the pad. The convective heat transfer between the surfaces of solid parts and the cooling airflow is simulated through conjugate heat transfer, and the discrete ordinates model captures the radiative heat exchange between solid surfaces. It is found that modeling the rotor rotation using the sliding mesh approach provides more realistic results than those obtained with the Multiple Reference Frames method.

Contamination protection of brake rotors has been a challenge for the auto industry for a long time. As contamination of a rotor causes corrosion, and that in turn causes many issues like pulsation and excessive wear of rotors and linings, a rotor splash protection shield became a common part for most vehicles. While the rotor splash shield provides contamination protection for the brake rotor, it makes brake cooling performance worse because it blocks air reaching the brake rotor. Therefore, balancing between contamination protection and enabling brake cooling has become a key critical factor when the splash shield is designed. Although the analysis capability of brake cooling performance has become quite reliable, due to lack of technology to predict contamination patterns, the design of the splash protection shield has relied on engineering judgment and/or vehicle tests. Optimization opportunities were restricted by cost and time associated with vehicle tests.

The approaching corporate average fuel economy (CAFE) regulations will again increase with new model years (MY). The U.S. Government finalized a regulation requiring cars and light trucks average 54.5 mpg fuel economy for MY2025. Vehicle manufacturers recognize removing weight is a key feature to meeting their targets for fuel economy and emission reductions. One common OEM strategy is the implementation of incremental weight reductions to attain these goals. The automotive industry continues to look for opportunities to reduce weight and cost while continually increasing performance and safety. Lightweighting technologies enhance vehicle performance, (fuel economy, acceleration, braking and emissions). New materials are available to reduce weight; however the incremental cost for the weight reduction can be prohibitive. This study will encompass the utilization of lightweight materials, as well as current and evolving manufacturing processes.

We propose a composite thermal model of the vehicle passenger compartment that can be used to predict and analyze thermal comfort of the occupants of a vehicle. Physical model is developed using heat flow in and out of the passenger compartment space, comprised of glasses, roof, seats, dashboard, etc. Use of a model under a wide variety of test conditions have shown high sensitivity of compartment air temperature to changes in the outside air temperature, solar heat load, temperature and mass flow of duct outlet air from the climate control system of a vehicle. Use of this model has subsequently reduced empiricism and extensive experimental tests for design and tuning of the automatic climate control system. Simulation of the model allowed several changes to the designs well before the prototype hardware is available.

An automotive cockpit module is a complex assembly, which consists of components and sub-systems. The critical systems in the cockpit module are the instrument panel (IP), the floor console, and door trim assemblies, which consist of many plastic trims. Stiffness is one of the most important parameters for the plastic trims' design, and it should be optimum to meet all the three functional requirements of safety, vibration and durability. This paper presents how the CAE application and various other techniques are used efficiently to predict the stiffness, and the strength of automotive cockpit systems, which will reduce the product development cycle time and cost. The implicit solver is used for the most of the stiffness analysis, and the explicit techniques are used in highly non-linear situations. This paper also shows the correlations of the CAE results and the physical test results, which will give more confidence in product design and reduce the cost of prototype testing.

This paper discusses simplified lumped parameter thermal modeling of power train components. In particular, it discusses the tradeoff between model complexity and the ability to correlate the predicted temperatures and flow rates with measured data. The benefits and problems associated with using a three lumped mass model are explained and the value of this simpler model is promoted. The process for correlation and optimization using modern software tools is explained. Examples of models for engines and transmissions are illustrated along with their predictive abilities over typical driving cycles.

In order to increase the efficiency of automotive turbochargers at low speed without compromising the performance at maximum boost conditions, variable geometry compressor (VGC) systems, based on either variable inlet guide vanes or variable geometry diffusers, have been recently considered as a future design option for automotive turbochargers. This work presents a modeling, analysis and optimization study for a Diesel engine equipped with a variable geometry compressor that help understand the potentials of such technology and develop control algorithms for the VGC systems,. A cycle-averaged engine system model, validated on experimental data, is used to predict the most important variables characterizing the intake and exhaust systems (i.e., mass flow rates, pressures, temperatures) and engine performance (i.e., torque, BMEP, volumetric efficiency), in steady-state and transient conditions.

Although electrochemical batteries are the mainstream for hybrid vehicle energy storage, there is continuing interest in alternative storage technologies. Alternative energy storage systems (AESS), in the form of mechanical flywheels or hydraulic accumulators, offer the potential to reduce the vehicle costs, compared to the use of electrochemical batteries. In order to maximize the benefits of mechanical or hydraulic energy storage, the system design must maximize the energy recuperation through regenerative braking and the use of the energy stored with high roundtrip efficiency, while minimizing system volume, weight and cost. This paper presents a design procedure for alternative energy storage systems for mild-hybrid vehicles, considering parallel hybrid architecture. The procedure is applied with focus on the definition of design parameters and attributes for a hydraulic AESS with high pressure accumulator.

Energy management plays a key role in achieving higher fuel economy for plug-in hybrid electric vehicle (PHEV) technology; the state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining the fuel consumed. The energy management algorithm should be designed to meet all driving scenarios while achieving the best possible fuel economy. The knowledge of the power requirement during a driving trip is necessary to achieve the best fuel economy results; performance of the energy management algorithm is closely related to the amount of information available in the form of road grade, velocity profiles, trip distance, weather characteristics and other exogenous factors. Intelligent transportation systems (ITS) allow vehicles to communicate with one another and the infrastructure to collect data about surrounding, and forecast the expected events, e.g., traffic condition, turns, road grade, and weather forecast.