Browse Topic: Trucks

Items (5,929)
Commercial vehicle operation faces challenges from driver distraction associated with traditional Human-Machine Interfaces (HMIs) and inconsistent network connectivity, particularly in long-haul scenarios. This paper addresses these issues through the development and presentation of an embedded, offline AI-powered voice assistant. The system is designed to reduce driver distraction and enhance operational efficiency by enabling hands-free control of vehicle functions and access to critical information, irrespective of internet availability. The technical approach involves a three-tier architecture comprising an Android-based In-Vehicle Infotainment (IVI) unit for primary user interaction and voice processing, an Android mobile device acting as a communication bridge and processing hub, and a proprietary OBD-II dongle for CAN bus interfacing. Offline speech recognition is achieved using embedded wake word detection and speech-to-intent engines. A user-centered design methodology
De Oliveira Nelson, RafaelDe Almeida, Lucas GomesArantes Levenhagen, Ivan
The deployment of autonomous trucks in off-road environments poses significant engineering challenges due to terrain variability and dynamic operating conditions. While recent advancements in perception, planning, and control architectures have improved vehicle autonomy, experimental validations comparing autonomous and manual control particularly regarding propulsion efficiency remain limited. This study addresses this gap by conducting structured field experiments to evaluate the performance of a heavy-duty truck operating in autonomous and manual modes. Tests were performed on a dedicated proving ground using a multi-sensor autonomous system. Key performance indicators included vehicle speed stability, engine speed regulation, and fuel consumption. The results show that autonomous driving achieved a 4.5% reduction in fuel consumption compared to manual operation. This gain is attributed to the system’s ability to maintain lower speed variance and more consistent engine behavior
Paula Silva, CiriloYoshioka, Leopoldo RidekiKitani, Edson CaoruAndré, Fatec SantoSilva, Nouriandres Liborio
At present, bulky waste is mainly collected and transported by self-owned vehicles. However, the use of self-owned vehicles for collection has problems, such as high purchase costs and insufficient stability in vehicle configuration, making it difficult to balance the utilization of truck resources and the efficiency of bulky waste collection and transportation. Therefore, this paper proposes a bulky waste collection and transportation model using shared vehicles. Under this model, a scheduling model for shared bulky waste collection and transportation vehicles is designed. The core of the model is to integrate time window constraints and three-dimensional loading constraints. By integrating existing truck resources for scheduling and optimizing the truck scheduling decisions through optimization algorithms, the feasibility and effectiveness of the model are verified through experiments.
Xu, ChenMa, Huimin
Although the number of trucks is low, their accident rate is high, and the consequences of accidents are severe. This paper is based on GPS data from 100 trucks, with each trip chain defined by a vehicle’s stay time greater than 20 minutes. The kinematic parameters for each trip chain are then extracted, and the entropy weight method is used to calculate the weights of various parameters. A random forest model is applied to select 11 key indicators, including speed and acceleration. The entropy weight-TOPSIS algorithm is used to assess the risk of each trip chain for the trucks. Different combinations of continuous and discontinuous trip chain scenarios are constructed. Finally, support vector machines (SVM) and decision tree methods are used for risk prediction under different trip chain combinations. The results show that the 11 selected key indicators provide an accuracy of 95.74% for describing the sample. In general, the SVM model shows better prediction accuracy than the decision
Huang, YunheXiong, ZhihuaLi, Jiayu
Large-spacing truck platooning offers a balance between operational safety and fuel savings. To enhance its performance in windy environments, this study designs a control system integrating both longitudinal and lateral motions. The longitudinal control module regulates the inter-vehicle spacing within a desired range while generating a fuel-optimal torque profile by minimizing unnecessary decelerations and accelerations. The lateral control module ensures lateral stability and maintains alignment between the trucks to achieve the expected fuel savings. A two-truck platoon is simulated with a 3-sec time gap under varying wind conditions, using experimental data from the on-road cooperative truck platooning trials conducted in Canada. The control system effectively remains spacing errors within the preset safety buffer and limits lateral offsets to 0.07 m, ensuring safe and stable platooning in windy environments. Additionally, the smoother speed profiles and reduced lateral offsets
Jiang, LuoShahbakhti, Mahdi
Stoneridge displayed its vision for the future of commercial vehicle technology on the SAE COMVEC 2025 exhibit floor. The Innovation Truck showcases the Tier 1 supplier's next-generation vision and driver-assistance technologies designed to enhance driver safety and fleet optimization. Mario Gafencu, product design and evaluation specialist at Stoneridge, gave Truck & Off-Highway Engineering a tech truck walkaround at the event. The first technology Gafencu detailed was the second-generation MirrorEye camera monitor system that's designed to replace the glass mirrors on the sides of a truck.
Gehm, Ryan
Vehicle manufacturers are to reduce the CO₂ emissions of new trucks dramatically within the next decade. That requires to consider emission-free/neutral vehicles in the fleet mix. Especially for the application of heavy-duty (HD) long haul trucks, fuel cell powered trucks demand a holistic concept for the integration of the entire powertrain, its auxiliaries and the complete vehicle’s energy management. In an internally funded research project, AVL built up a Fuel Cell Technology Demonstrator Truck. This vehicle is not intended to go into series production but to show leading-edge solution to challenges these vehicles are facing today. Due to the length restrictions of semi-trailer trucks in Europe, packaging into the chassis without having a rack behind the cabin is an issue as well as the ambient temperature level, at which the fuel system is to be derated. Solutions are highlighted in the article how to reach the performance of today’s standard diesel trucks. Furthermore, the
Döbereiner, RolfSchörghuber, ChristophSchenk, AlexanderSchubert, ThomasStöckl, Bernhard
Heavy-duty mining is a highly demanding sector within the trucking industry. Mining companies are allocated coal mine sites, and fleet operators are responsible for efficiently extracting ore within the given timeframe. To achieve this, companies deploy dumper trucks that operate in three shifts daily to transport payloads out of the site. Consequently, uptime is crucial, necessitating trucks with exceptionally robust powertrains. The profitability of mining operations hinges on the efficient utilization of these dumper trucks. Fuel consumption in these mines constitutes a significant portion of total expenses. Utilizing LNG as a fuel can help reduce operational fuel costs, thereby enhancing customer profitability. Additionally, employing LNG offers the potential to lower the CO2 footprint of mining operations. This paper outlines the creation of a data-driven duty cycle for mining vehicles and the simulation methodology used to accurately size LNG powertrain components, with a focus
John, Ann VeenaPendharkar, Koustubh
The key performance evaluation criteria for any automotive exhaust system are pass-by noise (PBN), exhaust backpressure, durability and reliability, exhaust brake performance, aesthetics (if visible from outside the chassis), cost, weight and safety. Also, with changes in emission norms, emission from Exhaust Aftertreatment Systems (EATS) is one of the crucial parameters while designing the exhaust system. This paper covers a critical problem faced during the Beta Proto Build and Testing phase of exhaust tail pipe assembly. The exhaust tail pipe assembly had loose fitting issues, which can cause problems during the functioning of the truck. Parameters like material of the pipe, length of strap, tightening torque and tolerance of the pipe diameter were considered to resolve the fitment issue. The resolution is done with the help of Design of Experiments (DoE) and Pugh Matrix Analysis based on QDCFSS (Quality, Design, Cost, Feature, Safety and Sustainability). Design for Assembly (DFA
P, Balu MukeshRokade, AdityaBiswas, Sanjoy
To provide needs of food, clothing and infrastructure for growing population of the world, off-highway vehicles such as those in construction, agriculture and commercial landscaping are moving towards electrification for enhanced precision, productivity, efficiency and sustainability. It has also paved way to adopt autonomy of these vehicles to address challenges like skilled labour shortage for timely and efficient execution. There are many challenges and opportunities of electrification in off-highway domain, be it through completely replacing engine in vehicles or efficiency improvements using hybrid architecture for powertrain and auxiliary power demands, electrification being key enabler precision and speed of the complex operations, automation of complex operation. This paper explains the need of electrification in electric off-highway vehicles and shows how the electrification solves the current challenges faced by off-highway heroes like farmers, construction site owners and
Deshpande, Chinmay VasudevMujumdar, ChaitanyaBachhav, Kiran
This study proposes a novel control strategy for a semi-active truck suspension system using an integral–derivative-tilted (ID-T) controller, developed as a modification of the TID controller. The ant colony optimization (ACO) algorithm is employed to tune the controller parameters. Performance is evaluated on an eight-degrees-of-freedom semi-active suspension system equipped with MR dampers. The objective is to minimize essential dynamic responses (displacement, velocity, and acceleration) of the sprung mass, cabin, and seat. The controller also considers the nonlinear effects including suspension travel, pitch dynamics, dynamic tire loads, and seat-level vibration dose value (VDV). System performance is assessed under both single bump and random road excitations. The ACO-tuned ID-T controller is compared against passive suspension, MR passive (OFF/ON), and ACO-tuned PID and TID controllers. Simulation results demonstrate that the proposed controller achieves superior performance in
Gad, S.Metered, H.Bassiuny, A. M.
On highways, platoons of semi-trucks are a common phenomenon. By maintaining a small headway, these platoons can effectively reduce air resistance, thereby improving fuel efficiency and reducing carbon emissions. However, this driving mode is also accompanied by many safety and operational risks, such as increased risk of rear-end collisions, reduced driving comfort, and susceptibility to interference from other vehicles outside the platoon. Therefore, behavioral analysis and evaluation of semi-truck platoons naturally formed in real traffic environments are of great significance for improving their driving safety, comfort and stability. This study focuses on the headway characteristics of semi-truck platoons, analyzes their headway distribution, headway gap and braking response behavior, and then proposes a safe headway threshold for emergency braking to effectively reduce the probability of rear-end collisions. In addition, the study also defines an optimal headway range to reduce
Hu, XiaoqiangCao, Qiang
As an important bridge connecting cities and rural areas, highway transportation has an irreplaceable role in regional economic development [1]. Accompanied by the booming development of long-distance transportation industry, strengthening highway transportation is of great significance to improve people's living standards [2], but because of the special characteristics of truck transportation, fuel theft is frequent, seriously endangering the driver's life and the safety of goods transportation, although the police in the severe crackdown, but fuel theft seems to be in addition to inexhaustible, truck drivers lose oil incidents still occur from time to time, due to the increasingly serious energy problems, the world's countries have Due to the increasingly serious energy problems, countries around the world have formulated strict automotive fuel consumption rate (hereinafter referred to as fuel consumption) regulations [3], in the transportation process to prevent fuel theft is of
Liu, YuzhenDuan, ShuWen
The objective of this trial was to compare the energy efficiency and performance of battery electric and conventional diesel tractors. Controlled road tests replicating normal operations were conducted using two electric and two diesel day-cab tractors. The test protocol was based on the TMC - Type III RP 1103A and SAE J1526 test procedures. The tests were conducted on a 110 km long route that included a 59 km hilly portion with a maximum altitude difference of 307 m. The tractors were divided into test groups of two vehicles. Trailers and drivers were switched throughout the trial between the tractors in a test group. The tests found that the two electric trucks consumed 60% and 63% less energy than their counterpart diesel trucks, respectively. Considering the average emission factor for production of electricity in Canada, the electric trucks emitted on average 82% less GHG emissions than the conventional diesel-powered tractors. The two diesel trucks showed similar fuel consumption
Surcel, Marius-DorinPartington, MarkTanguay-Laflèche, MaximeSchumacher, Richard
Like those in many other industries, truck and off-highway vehicle manufacturers face the challenge of producing quality components and maintaining productive processes while also generating a better bottom line. Improving employee training, simplifying complex operations and implementing better workflows can all help generate efficiencies. While not a new concept, lightweighting - in this case, reducing the weight of parts through the substitution of traditional steel with high-strength, thinner steels - can also be a viable answer to a better vehicle. As a rule of thumb, when manufacturers double the strength of the material through lightweighting, it is possible to reduce the weight of the part by one-third. That weight reduction can then lower the cost per part for greater profitability per piece of equipment and greater annual savings.
Gugel, Mick
To say 2025 has been a bumpy ride for North American electric vehicle OEMs would be an understatement not heard since Jack Swigert informed Houston that Apollo 13 was experiencing a problem. However, despite a tariff tug of war, EPA upheaval and continually changing tax incentives, OEMs are pushing ahead with plans to electrify the commercial truck segment. In late August, ZM Trucks celebrated the grand opening of its U.S. headquarters and assembly facility in Fontana, California. Truck & Off-Highway Engineering was in attendance for the opening ceremony, which included the U.S. debut of the ZM8 Class 4/5 truck.
Wolfe, Matt
The powertrain landscape of the future is sure to be a mix that includes clean diesel engines and other ICE options running alternative fuels. Zero-emissions technology such as battery-electric also will play a greater role in certain applications - despite the policy headwinds it currently faces in the U.S. “Eventually we have to decarbonize the heavy-duty industry,” Thomas Howell, segment lead for conventional powertrain, AVL in the U.S., told Truck & Off-Highway Engineering. A promising “best of both worlds” technology could be hybrid-electric. But as with BEVs, its impact will depend greatly on finding the right applications for it, Howell said. Read on for more of his thoughts on the hybridization of commercial vehicles.
Gehm, Ryan
Smarter control architectures including CAN- and LIN-based multiplexing can elevate operational efficiency, customization and end-user experience. From long-haul Class 8 trucks navigating cross-country routes to articulated dump trucks operating deep in a mining pit, the need for smarter, more reliable and more efficient control systems has never been more critical. Across both on- and off-highway commercial vehicle segments, OEMs are re-evaluating how operators interact with machines - and how those systems can be made more robust, flexible and digitally connected. Suppliers have responded to this industry-wide shift with new solutions that reduce complexity, improve durability and help customers future-proof their vehicle architectures. For example, Eaton's latest advancement is the E33 Sealed Multiplexed (MUX) Rocker Switch Module (eSM) - a sealed, modular switch solution that replaces traditional electromechanical designs with a multiplexed digital interface. Combined with Eaton's
Ortega, Carlos
In the commercial and off-highway sectors, equipment reliability isn't just a maintenance target but a business imperative. Whether it's a long-haul truck on the interstate or a dozer working through dust and rock, these machines operate in some of the most demanding environments on Earth. And while engine design and fuel choice often dominate conversations about performance, the role of grease is just as critical, particularly as equipment is pushed harder and longer under more variable conditions. Over the last decade, heavy-duty grease development has undergone a quiet evolution. Performance expectations have risen sharply. So have the environmental and regulatory considerations that influence formulation decisions.
Kumar, Anoop
The Front Axle wheel end assembly is a critical component of Vehicle functionality, comprising a wheel hub positioned to rotate smoothly on an Axle spindle. This rotational movement is enabled by bearings positioned between the hub and the spindle, allowing for frictionless rotation. The Front Axle wheel ends’ temperature typically depends on several factors such as type of Vehicle, Load & driving conditions and health of the components involved. In general, the wheel ends can become warm during normal operation owing to friction generated by the rotation of the wheels and the interaction of various mechanical components such as Bearings and Brakes. However, if the temperature of the wheel ends becomes excessively hot, it could indicate potential issues such as Overheating brakes, Wheel bearing problems, improperly inflated tyres, and faulty components. As temperature rise, materials tend to expand. This expansion can affect the dimensions of critical components in the Front Axle wheel
Pandiyan, MahendranJayaraman, KarthikR, SabariB, EllavarasanBhanja, Subrat Kumar
As the pressure increases to move to renewable carbon-neutral fuel sources, especially in heavy-duty diesel engine applications, hydrotreated vegetable oil (HVO) has shown to be an attractive alternative fuel to fossil diesel. Therefore, this study investigated the impacts of HVO used as a drop-in fuel on performance and emissions of a nonroad heavy-duty diesel engine by running back-to-back D2 ISO 8178 cycles with ultra-low sulfur diesel (ULSD) and HVO. The measurement results showed that brake specific fuel consumption with respect to mass reduced by 1.1%–3.6% switching from ULSD to HVO due to greater heating values of HVO, which is supported by 0.7%–3.5% lower CO2 emissions recorded with HVO. Conversely, brake specific fuel consumption with respect to volume increased by 0.3%–2.9% with HVO because of its smaller density. Combustion analysis revealed that combustion of both fuels is comparable at high loads while HVO ignites earlier at low power. Thus, lesser reductions in NOx
Duva, Berk CanAbat, BryanEngelhardt, Jens
This study presents a novel approach for predicting fuel consumption in heavy-duty vehicles using a Machine Learning-based model, which is based on feedforward neural network (FFNN). The model is designed to enhance real-time vehicle monitoring, optimize route planning, and reduce both operational costs and environmental impact, making it particularly suitable for fleet management applications. Unlike traditional physics-based approaches, the FFNN relies solely on a refined selection of input variables, including vehicle speed, acceleration, altitude, road slope, ambient temperature, and engine power. Additionally, vehicle mass is estimated using a methodology presented elsewhere and is included as an input for a better generalization of the consumption model. This parameter significantly impacts fuel consumption and is particularly challenging to obtain for heavy-duty vehicles. Engine power is derived from both engine torque and speed (RPM), ensuring a direct relationship with fuel
Vicinanza, MatteoPandolfi, AlfonsoArsie, IvanGiannetti, FlavioPolverino, PierpaoloEsposito, AlfonsoPaolino, AntonioAdinolfi, Ennio AndreaPianese, CesareFrasci, Valentino
Electrification of heavy-duty on-road trucks used for regional freight transportation is a viable option for fleets to reduce operation and maintenance costs and lower their carbon footprint. However, there is considerable uncertainty in projecting their daily range because highly variable payload mass, among other factors, confounds battery state of charge (SOC) prediction algorithms. Previous work by the authors proposed an electric vehicle range prediction model based on two parallel recurrent neural networks (RNNs). The first RNN used mean-variance estimation to output a predicted mean and variance, and the second used bounded interval estimation to provide bounds on the SOC required to complete a trip. The dual RNN approach resulted in estimating the remaining range and error bands of the SOC over the route. The previous work was limited because it did not incorporate driving conditions, like road type and ambient temperature, that affect driver behavior and energy consumption
Jayaprakash, BharatEagon, MatthewNorthrop, William F.
Fuel cell hybrid electric vehicles (FCHEVs) are a promising solution for decarbonizing heavy-duty transport by combining hydrogen fuel cells with battery storage to deliver long range, fast refuelling, and high payload capacity. However, many existing simulation models rely on outdated fuel cell parameters, limiting their ability to reflect recent technological improvements and accurately predict system-level performance. This study addresses this gap by integrating a state-of-the-art, physics-based model of a polymer electrolyte membrane fuel cell (PEMFC) into an open-source heavy-duty vehicle simulation framework. The updated model incorporates recent advancements in catalyst design and membrane conductivity, enabling improved representation of electrochemical behavior and real-time compressor control. Model performance was evaluated over a realistic 120 km long-haul drive cycle. Compared to the traditional fuel cell model, the updated system demonstrated up to 20% lower hydrogen
Dursun, BeyzaJohansson, MaxTunestal, Peraronsson, UlfEriksson, LarsAndersson, Oivind
The need for greenhouse gas emission reductions leads to decreasing emission limits in road traffic. The development of efficient powertrains and the use of renewable energy sources are crucial in order to meet these targets. Electrification is one of the key technologies that can help to achieve higher efficiency and lower emissions. Besides the passenger car segment, electrification has started to play a more important role in heavy-duty applications as well. One technology that has been discussed in the last years is the electrification of heavy-duty semi-trailers. In the joint research project "evTrailer2" funded by the German Federal Ministry for Economic Affairs and Climate Action, the potential of different technologies for electrified semi-trailer systems in long-haul applications is evaluated. The overall project goal is the development of high-efficiency technologies to help reduce the fuel consumption and therefore the greenhouse gas impact of large semi-trailer trucks. The
Knaup, LarsBeidl, Christian
This article presents a novel mechanical model for simulating the behavior of pavement deflection measuring systems (PDMS). The accuracy of the model was validated by comparing the acceleration of the new model with the data achieved through experimental tests fusing a deflection measurement system mounted on a Ford F-150 truck. The experimental test for the PDMS is carried out on a random road profile, generated by an inertial profiler, over a 7.4-mile (12 km) loop around a lake near Austin, Texas. Integrating a reliability-based optimization (RBO) algorithm in a PDMS aims to optimize system parameters and reduce vibrations effectively. The PDMS noises and uncertainties make it crucial to use a robust system to ensure the stability of the system. This article presents a robust algorithm for considering the uncertainties of PDMS parameters, including the damping coefficients and spring stiffness of the supporting brackets. Moreover, it considers the variation of system parameters, such
Yarmohammadisatri, SadeghSandu, CorinaClaudel, Christian
University of Waterloo researchers are tapping into idled electric vehicles (EVs) to act as mobile generators and help power overworked and aging electricity grids.
Long-haul truck drivers are mandated to take off-duty time of 10 h (a.k.a. hoteling) before driving. During the hotel phase, drivers spend time inside their trucks (sleeper cabs) and idle the internal combustion engine for comfort by utilizing the heating, ventilation, air-conditioning (HVAC), and other onboard appliances. For one 10-h period, the average cost is about $40, which can be a lot when considering a million truck drivers idling overnight. SuperTruck II is a 48 V mild-hybrid heavy-duty truck with auxiliary loads powered by an onboard battery pack. An optimal control algorithm is developed to charge the battery pack during the drive phase up to a certain state-of-charge (SOC) level, sufficient to meet the power demands of the auxiliary load during the hotel phase. This article captures the research done to predict energy consumption in a mild-hybrid heavy-duty sleeper truck during hoteling. Physics-based gray box models are developed to estimate the power consumption of an
Khuntia, SatvikHanif, AtharAhmed, QadeerLahti, JohnJorgensen, Iner
The transportation and mobility industry trend toward electrification is rapidly evolving and in this specific scenario, wind noise aeroacoustics becomes one of the major concerns for OEMs, as new propulsion systems are notably quieter than traditional ones. There is, however, very limited references available in the literature regarding validation of computational fluid dynamics (CFD) simulations applied to the prediction of aeroacoustics contribution to the noise generated by large commercial trucks. Thus, in this work, high-fidelity CFD simulations are performed using lattice Boltzmann method (LBM), which uses very large eddy simulation (VLES) turbulence model and compared to on-road physical tests of a heavy-duty truck to validate the approach. Furthermore, the effect of realistic wind conditions is also analyzed. Two different truck configurations are considered: one with side mirror (Case A) and the other without (Case B) side mirrors. The main focus of this work is to assess the
Guleria, AbhishekNovacek, JustinIhi, RafaelFougere, NicolasDasarathan, Devaraj
To achieve accurate and stable path tracking for unmanned mining trucks in the face of changing paths and response delays in steering, this study raised a lateral control strategy for unmanned mining trucks based on MPC and considering steering delay response characteristics. Under the basis of deriving the state space equation from the commonly used two degrees of freedom truck dynamics model, this method introduces the dynamic relationship between steering angle issuance and actual response to form an augmented form of state vector to overcome the control instability caused by steering response delay. Then, based on the MPC method, a constrained objective function is constructed to solve for the optimal control law. In response to the problem of inaccurate selection of prediction and control time domains, this article proposes an adaptive selection method for prediction and control time horizon based on a modified particle swarm optimization (MPSO) algorithm, which obtains the
Mao, LiboWu, GuangqiangGui, Yuhui
This research primarily addresses the issue of resistance model setting for chassis dynamometers or EIL (engine-hardware-in-the-loop) systems under various loads. Based on the data available from the heavy-duty commercial vehicle coast-down test reports, this article proposes three methods for estimating coasting resistance. For heavy-duty commercial vehicles that have not undergone the coast-down test, this article proposes the GA-GRNN (AC) model to predict coasting resistance. Compared to the GA-BPNN model proposed by previous studies, the new model, which achieves 93% prediction accuracy, demonstrates higher estimation accuracy. For heavy-duty commercial vehicles that have undergone the coast-down test, the coasting equal power method proposed in this article can estimate the coasting resistance under various loads. The accuracy and stability of the new method are verified by several coast-down tests. Compared to the existing method proposed by existing scholars, the new method has
Liang, XingyuSun, ShangfengLi, TengtengZhao, Jianfu
The development of modern road implements demands rigorous and comprehensive analyses of various design aspects, including the dynamic behavior of vehicles and the structural durability of their components. Multi-Body System Simulation (MBS) has become an essential tool in developing efficient products, allowing engineers to virtually assess how a truck + semi-trailer combination responds to different operational and loading conditions. By employing models that account for detailed interactions among various vehicle systems -such as suspension, chassis, axles, and fifth wheel-vehicle dynamics can be investigated in complex scenarios. These scenarios replicate real road usage, abrupt maneuvers, and special testing tracks, providing insights into performance under demanding conditions. This approach also facilitates the cascading of loads between systems to conduct durability calculations and estimate the operational lifespan of the implement. This study introduces a development cycle
Justo, GabrielCrocoli, MicaelVigânico, CarlosPio, Frederico Nodari
Mercedes-Benz Trucks employs “like-new” reworked batteries to expand its spare parts portfolio and to inform future battery designs that are more sustainable. Remanufacturing engines for medium- and heavy-duty trucks is nothing new to the industry. Reworking high-voltage batteries for reuse in electric trucks is a newer practice. Used batteries are often recycled or find a second life in stationary energy storage systems. Mercedes-Benz Trucks is all in on the approach, launching the new reworked CB400 battery for first-generation eActros 300/400 and eEconic trucks. The so-called “Genuine Reworked Batteries” offer a resource-efficient and economically attractive alternative to brand-new replacement batteries, the manufacturer says, providing customers with like-new quality, tested safety and full functionality.
Gehm, Ryan
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