Lanika Solutions

04/06/2026

MapleSim Used to Create High Fidelity Physical Models of Hybrid and Electric Vehicle Batteries - User Case Study

Dr. Thanh-Son Dao and Mr. Aden Seaman are working with Dr. John McPhee, the NSERC/Toyota/Maplesoft Industrial Research Chair for Mathematics-based Modeling and Design, to develop high-fidelity models of hybrid-electric and electric vehicles, including the batteries. They chose MapleSim because they have found the symbolic approach in MapleSim to be an effective way to develop simulation models that have fast real-time speeds for hardware in the loop (HIL) testing and very high fidelity compared to models created in conventional modeling tools.

Battery Electric Vehicle (BEV) Model

Using MapleSim, Dr. McPhee and Mr. Seaman designed a math-based model of a complete battery pack, and then developed simple power controller, motor/generator, terrain, and drive-cycle models. The resulting differential equations were simplified symbolically and then simulated numerically. A variety of driving conditions were simulated, such as hard and gentle acceleration and driving up and down hills. The results were physically consistent and clearly demonstrated the tight coupling between the battery and the movement of the vehicle. This model will form the basis for a more comprehensive vehicle model, which will include a more sophisticated power controller and more complex motor, terrain, and drive-cycle models.

Hybrid-Electric Vehicle (HEV) Model
Dr. McPhee, Dr. Dao, and Mr. Seaman used MapleSim to develop a multi-domain model of a series HEV, including an automatically generated optimized set of governing equations. The HEV model consists of a mean-value internal combustion engine (ICE), DC motors driven by a chemistry-based NiMH battery pack, and a multibody vehicle model. Simulations were then used to demonstrate the performance of the developed HEV system. Simulation results showed that the model is viable and, as a result of MapleSim’s lossless symbolic techniques for automatically producing an optimal set of equations, the number of governing equations was significantly reduced, resulting in a computationally efficient system. This HEV model can be used for design, control, and prediction of vehicle handling performance under different driving scenarios. The model can also be used for sensitivity analysis, model reduction, and real-time applications such as hardware-in-the-loop (HIL) simulations.

“With the use of MapleSim, the development time of these models is significantly reduced, and the system representations are much closer to the physics of the actual systems,” said Dr. John McPhee. “We firmly believe that a math-based approach is the best and quite possibly the only feasible approach for tackling the design problems associated with complex systems such as electric and hybrid-electric vehicles.”

Read case study → https://lnkd.in/gJUcH4un

03/06/2026

MapleSim | Event Handling for Real-time Simulation with Hybrid Systems - Whitepaper

Highlights:
▪ Learn how new techniques in event handling are making complex simulations more accurate and stable
▪ Discover why new approaches to event handling are becoming necessary for modern engineering designs
▪ Understand how a fixed-step numerical integrator solver can be used for real-time simulation projects

This whitepaper will introduce a new approach to handle events which is needed to simulate hybrid systems in a more stable and accurate manner. The approach is designed for a fixed-step numerical integration solver for real-time simulation applications.

Download your free whitepaper → https://lnkd.in/gECkZ2Cj

02/06/2026

MapleSim | Battery Innovation: Modeling and Simulation of Electric Vehicles - Whitepaper

Highlights:
▪ See how MapleSim’s Battery Library can be used to create high-fidelity, efficient models for battery electric vehicles
▪ Understand the ways that models can be customized to your own needs and model the electrical, chemical, and thermal components of your system

The field of energy storage is extremely active with a constant stream of innovations being deployed to address some major design challenges. At the heart of this activity is the commercial drive to increase energy density, extend battery life, and improve overall charge and discharge efficiencies in order to reduce unit costs and enhance product reliability.

In particular, the electric vehicle industry is faced with major economic pressures to increase energy densities and hence reduce costs. There has been an increased focus on developing high efficiency, cost-effective electric vehicles whose performance is competitive with gas-powered cars, and as the price of oil rises and environmental concerns become more important, automotive companies are putting greater effort into electric and hybrid-electric vehicles (EV/HEV).

In this whitepaper, read about how math-based modeling techniques are used to design batteries for efficient electric vehicles.

Download your free whitepaper → https://lnkd.in/gfaZ3M_b

01/06/2026

MapleSim Driving Innovation in Vehicle Dynamics - Whitepaper

High performance physical modeling and simulation increases efficiency and productivity in vehicle design.

Highlights:
▪ Explore the benefits of employing a model-based design approach within the vehicle design process
▪ Discover how the use of model-based design and virtual prototyping allows automotive manufacturers to reduce design and prototyping costs significantly while fulfilling the demands of governments and markets

Vehicle manufacturers are constantly faced with the challenge of balancing fuel efficiency and safety against the demands for greater performance and lower development costs. Driven by these needs, a wide range of computer-aided modeling tools has emerged, covering all aspects of the dynamic behavior of vehicles. However, these tools tend to be very application-specific and use computationally intensive numerical methods, such as finite difference and finite elements. While these are useful for the "off-line" stages in the design process, where time-to-result is not too critical, there is an increasing demand for faster simulations to the point where high-fidelity models need to be run in real-time for hardware-in-the-loop (HIL) testing. The demand for better understanding of the dynamics, and the ability to produce high-fidelity physical models of vehicle systems that can be used in HIL systems to test prototype controllers, has reached a critical point for many companies. This article explores how the use of model-based design and virtual prototyping allows automotive manufacturers to reduce design and prototyping costs significantly while fulfilling the demands of governments and markets.

Download your free whitepaper → https://lnkd.in/gKPBiYwm

26/05/2026

APEX Intro (Part 1): Functions, Menus, Geometry Hierarchy

This introduction to APEX highlights common functions, definitions, geometry hierarchy, menus, and optical concepts. It also briefly discusses the 4-Step Workflow Process, which is used for any task inside APEX and is fully demonstrated in Part 2.

Request your free 15-day trial of APEX at [email protected]

Watch video →

This introduction to APEX highlights common functions, definitions,...

25/05/2026

Thermal Irradiance in ASAP (Part 2): First Look

Dr. Jon Herlocker answers a question arising from the Thermal Irradiance in ASAP: First Look video. How do we know the bolts within the example are the cause of the thermal irradiance found within the system depicted?

Request your free 15-day trial of ASAP at [email protected]

Watch video →

Dr. Jon Herlocker answers a question arising from the Thermal Irrad...

22/05/2026

Thermal Irradiance in ASAP (Part 1): First Look

Highlights the commands associated with the Thermal Irradiance feature introduced in ASAP 2025 V1. This video demonstrates how a small set of well-designed commands provides a complete and flexible analysis.

Watch video →

Highlights the commands associated with the Thermal Irradiance feat...

21/05/2026

Thermal Irradiance Applications - ASAP optical simulation software

Dr. Jon Herlocker provides insight and a wide range of applications for the Thermal Irradiance feature in ASAP.

Focal planes of cameras, telescopes and other optical devices that work at middle and far (thermal) infrared wavelengths are subjected to radiation emitted by warm surfaces within the device. It is often necessary to calculate the magnitude and distribution of this background radiation across the detector. Now, these calculations may be performed within the ASAP Thermal Environment.

Backwards ray tracing is the approach used within the ASAP Thermal Environment to calculate irradiance. Tracing backwards requires rays from only one plane rectangular object (the detector), and most if not all of the rays traced will intercept one or more objects that contribute to the thermal irradiance. This new feature provides users with an additional tool to ensure optical systems operate as intended.

Watch video →

Dr. Jon Herlocker provides insight and a wide range of applications for the Thermal Irradiance feature in ASAP.Request a free ASAP 30-day trial at: https://s...

20/05/2026

Using ASAP Legacy Project Files in new versions of ASAP optical simulation software

Jon Herlocker demonstrates how to open legacy ASAP project files (*.apf, pre-2017) in newer versions of ASAP (*.apx, 2017-forward). It also shows how to run a legacy project file and how to save these files in newer versions of ASAP.

Watch video →

Jon Herlocker demonstrates how to open legacy ASAP project files (*.apf, pre-2017) in newer versions of ASAP (*.apx, 2017-forward). It also shows how to run...

19/05/2026

Gas Detection Sensor

The Gas Detection Sensor (GDS) is an aircraft or helicopter mountable, two-phased gas/leak detection sensor.

The GDS provides documentation and traceability via the internal Video and HD Cameras. Designed and engineered by Breault Research Organization (BRO), the GDS uses a sample of the gas of interest as a spectral filter.

Two radiometers — one with gas (correlation) cell in its optical path and the other without — focus on the ground through a narrow spectral absorption band (passband). The radiometer without the correlation cell, measures the total incoming radiance / flux within the passband (REF signal).

The radiometer with the correlation cell also measures incoming radiance / flux within the passband at the COR signal. By comparing the REF and COR signals, gas concentrations are retrieved. On-board cameras take pictures of the scene and sensors measure location and flight relevant data.
▪ ipeline Inspection
▪ Leak Detection
▪ Ethane and Methane Detection
▪ Hydrocarbon Detection

Learn more → https://lnkd.in/gVZuZxSK